{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image,ImageDraw\n",
    "import PIL.Image as IMG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import tanh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3 as sqlite"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TfmVLqWbPTmyzXmxsrGJjYzV5crxuuSVFL75Y1P6BAmFw/vx5HTlyxAhIdWU2KYvFossuu8wnIHX55ZfLarXKYrGEsXoAQCRccskl+vrXv665c+dq//79+vvf/y6Xy2XMRrV792599NFHSkpK0m233aahQ/1/yBJCLz8/3yec4nA4lJWV5TeoHB8fr/j4eCUmJurhhx8OeDagZrm5uT7bZGZm+g3OJCQkKDs722fmHrfb3WHQpju2bNkSUF3NP3fHx8crOTnZJwgUbgUFBbLZbG1mhrJarcrKyvJZ14xxzsnJMf7fMqDVrPnaGTdunE/wLC8vT8nJyX6vt0hem6HW0XhYrVYtXbpUEydO1Nq1X8x+XFpaqvT0dJ9QGNCTEZ4CAAAAAPRK06dPN77+6KOP1NTUpJiYGBMrAgAAQE/0+ecNfmf3eeDOuJDPPnXdlEv8zsJz8NPTeqGstkv7bC/ENGPKKCmMYZIXymr1vRVtl8cO716w51jt2S6PhSRNndw24CNJr2470OV9dldV9Qm9u+9c0NtV7j/pNzx1aTuzpQXig91Hu1TL+x8e8xue6qiW3nS9AwA691KrwM38+bfp5//9y4C2nT07Udtef1Nzb/5q0P22Duzk/PI3uvfeZQFt63Su0Ynjx42Zr/73//pXLVr0bb9hr3B55ZWX9Yc/bGwTnGpPJI63+fVm/oJTrcXGxgZcBxCM+vp61dbW6p///KeOHj2qo0ePGl9/9llws4ONHDnSCEc1B6XGjRunAQMGhKl6AEC0sFgsRsjhrrvu0pYtW7Rt2zY1NTWpqalJ27Zt044dO3T77bfrpptuIkAbZmVlZUZoRro4q08gM98kJiZq3bp1evjhhwPuq7y83Kev1NTUTgM6TqdTVVVVRhCmo6BNd2zbts2nnZyc3Ok2sbGxWrp0aUjr6Ijb7da6det8glP+mDnOa9as8RucaiktLU2bN2/2CTft3bvXmEmrWSSvzXBZt25dh+ORlJQku91uzPwlXZwNjPAUegvCUwAAAACAXmn06NG69NJLdfToUV24cEEHDhzQpEmTzC4LAAAAPczBTz1+QyELUyZrb/VnKn3vdMj6mjPTf7Bnh6vroY/2QkzjLuuZn5R7wN318b4jyeo3COf57POQB+GC8f6Hx7q03ZFj/j8x398xBsr1QeRq4Xrv2x566CHFxMSoX79+slgsPv+PiYkJ+r/O9tOVfUeqtpY1Ar2Vx+PR//5f/+qz7D/+87+D2sc11yTo//z7f7TZT2f9rv7RFzMnzZ9/W9ABnkWLl/iEhfbs2a2bbro5qH10x/z5tynl1vkBrdsbjhdoyev16ty5czp9+rTPfydPntSxY8d09OhRnThxQl6vN6j9Dhw40AhJNf83YcIEZhMBAEiShg0bprvuuks33XSTNm3apIqKCknSuXPn9Nxzz6miokJLly7VsGHDTK6099q8ebNPO5BwSrPExESlpqYGPPvSpk2bfNrp6ekBbXfXXXcZs/hI/oM23dUyvCIp5OGsULDb7QEdt1njbLfblZSU1KW+ysvL2/QVyWszHAI9X3feeafP9VddXR3OsoCIIjwFAAAAAOi1rr76ah09elSStGfPHsJTAAAACNo/yg/7DU8NGtRf//rD2frm7qMqfGF/l2braW3q5FF+l4cj2DMidnBI93fdlEtkG3+JJl05TJcMGaBJV7adUSgUdu872eVtE672P7579x3v8j5DYW91cJ+I36y9oFB37K7yRKyWnny9o/vOnz9vdglRx2KxdCusFWzYy2KxGP9v+XUkl3Xntf8/e/ceF1Wd/w/8NVy94m1UVBgVCBXQdALKSrKRJS/lF8nctsjNlpLY6lvkbrPpt936al/clNytJSo2W2K3XdeQ2rxExdpYZoKjEWLQiDqOijoajDdUYH5/8OMsZ2aAMwPMmYHX8/Hw4Zwz55zPe845yjBzXufdus/a/t12P9o+72heZ393x7K2z/dV1dVVoulnVzyHkJBQp7dz113znApP2Y771H8/6/SYkZGTRNPffVfu1jDRopTFkpd11+t9dsVzWL9urTC9ZctmLFokvU7qO65du4bm5mY0NTWhqakJzc3NuHbtGq5evYorV67g6tWraGhoQENDAy5dumQXkrJYLGhsbHR5fIVCAaVSaReUUiqVws8SIiKi9owePRoZGRmorKzE5s2bUVvbcrOXiooKrFmzBg8//DAmTZrUyVbIWQaDQRTaUKvViIiIcGobCQkJkgIqtmOlp6dLDijZdu45dOhQt4enbJlMJo/r/jN79uxOl5FzP997772Sl7Udq20XKsC952ZPkbo/xowZI5q2DfIReTOGp8hjWCwW7N69GzU1NaIfDmq1GlFRUVCr1aIfTklJSaL1i4uLJY9lNptRVlZmN5ZGo0FkZCTi4+MlvcmwrUHq8x3VarFYUFVVhdLSUhiNRtEPndb6pk2b5vQPXbm0HtcDBw7Ytd2Mi4uT9EamK8fatg5H51d8fLzkY+6J43XX+dxWZ/u8tLQUpaWl0Ov1wptElUoltOzsrM1pdxxTwD37ue2/SdvX23pngs5eLxEREcln8uTJ0Ol0AHg3HCIiIiJyzXvba6G5PQSh4xyHgaZGjcLaqFEw1JzHV6Wn8N5217vmDB0S6HD+Z+/OcXmb7Qka7HiszmhmDMGksMFQjuiPsPFD0C/QDyOV7rtD+4la1wMX7QW6uhLI6g7d2b2sq7ojBCiVN5zvRO5ktVphtVrR3NwsdynUg17639/LXYIsDh06KJpOTLzLpe2Ehzv3HbntuLbBIClsL+o7esS9nzFOmzZd8rLuer2JiXeJwlOPPboMX+/+Cj9/+BeIjub3pvQfTz/9tFvGGTp0KEaNGiX8GT16NEaOHAmlUgk/P14aR0REXRMVFYWVK1di27Zt2LFjB6xWK+rr6/HHP/4RSUlJuPvuu+Hr6yt3mb2GwWAQTc+fP9/pbUi9ls92rGnTpkkew/aaxJMnT0peVyqNRiO65ragoAAZGRke1YFKyr6Wcz9PnDjR5bFsA0PuPDd7itT9YbsvbINkRN6MvyGSR8jPz0dBQYHD5/R6PfR6PQoKCqBWq/HEE090KQzR0VglJSUoKSlBbm4ukpOTsWTJEiiVSpfHcobFYsFnn32G3NzcdpdprQ9oeWOUlpbmtvpcsWPHDlEby7aKiopQVFQElUoFrVbbo2GwwsLCdvdr6/nVeswzMjK8ajx3n886nQ75+fkO3wwZjUYUFBSgoKAAGo2mx9+ou2M/dzSG0WiE0Wh023lMRERErmn74c+RI0fQ3NzMO0oSERERkdOWrSzD++tu6TAkFBE2HBFhw3F/8iRUHz6Pf31qdDoUM8qNISRnaGYMwT0/USEyfDgCA+X9aqkrQaN+7dTelUAWuc5Tz3dyj3Xr1qG5uVn0p6mpCVarVfS37TId/enq+lK301O1EfVmFy6IuywGBwe7Zdzvyr8VTYeHjevyNjduzMPvX3m1y9uRauTIUZKXddfrjY2Ns+s+tXFjHjZuzMO8eQuwKGUxZs26A0rlyC6PTxQQEIAhQ4YgKCgIQ4YMEf4olUohLBUQECB3mURE1Mv5+vrinnvuQWRkJN59913U19fDarXik08+gcFgwPLlyzFo0CC5y+wVbG+IGhYW5raxunLtX0lJCbRabVdLErn77rtF4amSkhIYDAYsXboUCQkJ3TqWq6RcHyrnfu7O66vdeW72FE++3pzIXRieIlmZzWZotVrJqVS9Xo9HHnkEOTk5PT5WUVER9Ho9srKyevwHRkVFBTZs2OBUOrf1jVB2drZHJclbZWVlid64tcdoNCIjIwN/+9vfun0/u3LMLRaLy29i3TmeHOdzR0EiWyUlJairq0NWVpZLY3XEHfvZ2TFaz2NXO2gRERFRzxkyZAhGjBiBc+fOoaGhAbW1tRg7dqzcZRERERGRF/rZij3IfWEGIsKGd7hcYKAfpkaNwtSoUXjoRD0++uQotujMksaQO5jkiJTX7C3aC795UuenvsQTz3dynwEDBshdgsexDVf1ZACsNQTW2umq7d+O5rn7OSnzWvdZ69+tj9ubL2VZV9ZxtGxHf/dVv33hedF0SEioW8bduDHPLeP0JGeuBXDn69VqVyEoaIjdsd2+fSu2b98KAFi2LI3dqKhD/v7+GDt2LMaMGYNBgwYJwai2QanAwEAoFAq5SyUiIgIATJo0CStXrsRf/vIXHDzY0vXz8OHDeOWVV/DLX/4So0ZJD76TY7bX6/XktbFFRUWi6aSkpB4byxUxMTF23aeMRiNWr14NAEhPT0dCQoKsgRgpx8fT97NU7jw3iajn8FsJko2jcIJKpcLixYsRExMj6i5lMBhQXFws/BB1NpDRGpxoO5ZarUZqaqqoDWJFRQUKCgqEdotGoxFarRZ5eY4/ZLQNStj+UJcapMjMzBTVNXv2bLt9YLFYcODAAVHXn9ZOP93RLak77dixQ3jDZvsGzWw2Y9u2bXbdkvLy8ro1ee/omEs5v0pKSly6mNad4/XU+dyRHTt2CMGp5ORkJCUlie4AYPtvFGgJOxYWFiIlJcXp8drjrv1sO4aj12yxWHDmzBmUl5dLDpURERGRPCZOnIhz584BaPnwmuEpIiIiInJV+kv7sShBiYV3TUDouCGdLh86bgh++ciNWHhXPV5/txL7frjshiq7h2bGEDybPt2pgMvVq404Y76EuvqrOF/XgDtuVfVghUREvYtCoYCfX8v/uf7+/jJXQz3FfO6i3CUQdZuMjCdxxx134i/v/tlhcKu1G9WzK55DWtpydqLqg1atWoULFy6gvr4eBoMBBw8exI8//ig8f/36dRw7dgz19fVYsmQJpk+fLl+xREREEg0aNAgZGRn4/PPPsWXLFlitVpw9exavvPIKli9f3qWuOgThWsdWfT2gotVqERkZ6fD6xNzcXOTm5jq8dpS6H89Not6B4SmSTV5eniicoNFokJGR4fAHSkREBCIiIhAXF4eVK1c61aEJAHJyckTrpKenOwx0xMTEICsrS9Q1yWg0dnsAxJHO3sAEBQUhISEBUVFReOCBB4T5RUVFWLhwoSg0Irfs7Gzhb9vXo1QqsXTpUkyYMEFIwAMtnYpSU1O77XXYHnMp51dCQgIyMzPtgl2eNp4c53NHxxT4z2sKDg4WvVHPzc1FYmJit71RdMd+3rFjh6T9GxQUhKCgIERERCAxMdHuDglERETkOcLCwlBWVgYAOHLkCGbNmiVzRURERETkzbbozNiiM2NRghJ3zQ6V1JUpdNwQvLQiDh8XH8YbH5jcUGXX3HTDgE6DU8dP1KPmWD2OHr+Ai5caHXbXYniKiIiIqHeLjo7B7195FT9/+BfQ68uQ+cyTdsusX7cW69etxc4vvmYXqj6m7Y3M4uPjYbVaUVtbiwMHDuDf//43Ll5sCZTW1dXhrbfewm233Yb77rsPAQEBcpVMREQkiUKhQGJiIkaPHo0///nPuHbtGi5duoQ//vGPeOihhxAXFyd3idSLpKSkID4+Hh999JHDaxT1ej30ej3UajXS0tIY4CMi6gDDUyQLnU4naiWpUqkkdR2Ki4vDmjVrsHLlSsljlZaWisZKTk7uNDii1WphMBiEAEV3B0BstRfOcESpVCI9PV0UUNm7d69HhacAYM2aNR0m2RMSEqBWq0Vp7IqKim55HRUVFS6dXzExMcjOzhZ1AvO08eQ8n1etWtXp3QlSUlKwbds2UfioqqqqW34hdNd+3rlzp2g6MTGx03WCgoKwdOlSSdsnIiIi9wsLCxMe19TUyFgJEREREfUmrSGqm24YgNm3jMJt8SEIGhzY7vKBgX64955JuHi5Ee9tr3VqrMSHP+9quU554uEoh8Gpq1cbUfLlMax/76hb66G+xd3nOxER9R1nzRfkLsGt3Pl6o6NjEB0dg//6rxR8++1+/OujIrtuVGuzVuP1P73FO7T3YQqFAmPGjMGYMWOg0Wig0+nw6aefCiGqr776CocPH8YvfvELjBs3TuZqiYiIOjd16lQ8++yzyMnJQX19PRobG7Fx40ZcuHABGo1G7vLIScXFxXKX0K6QkBBkZGRgyZIl0Ol0dtdoAi0hqoyMDKxatQoJCQkyVdo5T97PRNT7+chdAPVN27ZtE01LCUC0iouLQ3JysuTlP/jgA9F0amqqpPUWL14smq6qqpI8prOc7QIUHx8vmq6tde6L9p6mVqslhWXuvfde0XR3Xchq22HImfMrJibGqfPL3ePJdT6r1WrJb6htxyotLXVqrPa4az+zvSoREVHvM27cOPj7+wMAzpw5I3wRS0RERETUHfb9cBnr3zuKlCe/xJ/e+RaGmvMdLn9/8qR2nztrvuRw/k03DOhSjc7QzBiC0HFD7OZfvdqI9bkHvDo4Zblw1eH8RQlKN1dCgGec70RE5B7LlqWJpg8fNri0HZPpuFPLv/jSy6Jps/msS+N6C094vUFBQZg16w78/pVXUbjlY9Fz27dvxeefd/+Fkr39uPZWgYGB+MlPfoL//d//xa233irMr62txfr163HkyBEZqyMiIpIuNDQUv/rVr0QdFzdv3ozPPvtMxqq8l0ol7mRvNtt3u+8uarVaNG2xWHpsrO6iVCqRkpKCvLw8ZGdnOwzprV69GiaTSYbqHPPG/eyIO89NIuo5DE+R2xkMBlE4Qa1WO90mUmqIw3as9PR0yUEI2w47hw4dkl5gD7PtzuSoFaecbENR7RkzZoxo2ja04oruOL+SkpI8cjw5z2epx9TRWLZ3OHCFu49rW570iwQRERG5xtfXF+PHjxem2X2KiIiIiHrKFp0Z6S/tx5/e+bbdYEhgoB+efWiCw+carjY6nK8a474wyU9mjXU4f8++kyjZX++2OnpCvaXB4fyw8YPcXAkBnnG+ExGRe0yddqNourz8gEvbqTxY4dTytt9HHz161KVxvYWnvd5Zs+7A9h0lonlf7/6q0/WcDdfJ/TqpawIDA5Gamoqf//znCAgIAAA0NDTgtdde42f5RETkNYYPH45nn30WkZGRwrzCwkJ8+umnMlblnWyDNq40FjAYpL2ftA3DnDlzxumx5BQTEwOtVovs7Gy711JSUtLOWu7n7fu5lTvPTSLqOQxPkdvZ/uc/f/58p7dhG86QOta0adMkj2EbUDp58qTkdfu6iRMnSlrOdh93V8imLVfOL2dCOe4cT87zWeoxdTRWd4Xi2urJ/Wx7N4aCggKvvdsBERER/Ud4eLjwmF+4EhEREVFP26Iz42cr9rQboIqZ7LjTUc0xx+Gk+Okju622zgSPHuhw/lelzn2p7YndnGpPOz4eN0wc5uZKCPCM852IiNxjypRo0fRjjy5z6fu3goK/OLV8ZORk0fSmf/zN6TG9iSe+3tjYONH0xo15dsvYdsxyNlznCa+Tuu7mm2+GVqvFiBEjALQEqF5//XV+nk9ERF6jf//+yMjIEAWotmzZguLi7u+82ZuFhYWJpqurq53eRnl5uaTlbK9D9tZgS0xMDJ5++mnRvIKCAnmKcaC37Gd3nptE1HMYniK3s/1gw/YHSk+O5WynmrbkSGKbTCZUVFRAp9OhsLAQOTk5SEtLc7mDjrsolfJ9Ke7O88vd48l5Pst5TAH37ue7775bNF1SUoLMzEzodLoeG5OIiIh6XtswOL9sJSIiIiJ32fSR4y+CQ8cNcTj/6PELDudPumFEt9XUmfZqc7brlCd2c6r84UeH8yPChuOmG9jtyN084XwnIiL3iIycZDcvJ+ePTm0jJ+c1bN++1al1oqNjMG/eAmF648Y8bNmy2altAIDFYkFW1mqn1zObzzq9TlfI/XpdZdsxa0vhZsnhul27vnAYyHIHdx/fviA4OBhPP/00hg4dCqAlQPXGG2/g/Pnz8hZGREQkUUBAADIyMjBp0n/e/xYVFeGTTz6RsSrvYntNZG5urlM3XrBYLNi2bZukZaOiokTTmzc7/97ZU0htSCGH3rKf3XluElHPYXiK3M62u1BQUFCPjVVUVCSaTkpKcuqPuxkMBhQWFgoBqUceeQSZmZlYvXo1cnNzUVRU1C3dmXoz2y5Htl2QvHk8bzufu5M793NMTIxd9ymj0YjVq1cjKSkJhYWFMJvNPTY+ERER9Yy24aljx46hqalJxmqIiIiIqK/YonPuc6T3ttc6nB80OBCP39uzn3V2t9viPa/e97bX4urVRofPPfoz+4u6qWf1pvOdiIg6FhQUhOxXXxPNW79uLXJyXmtnDbGcnNfw2xeed2nsRx97XDT92KPLnAoUlZWV4olfPob169Z2umzb4BLQEuxxN3e83pyc1yQHh8rKSkXTz654zm6ZadOmi6a3b98qKVxXVlaKlEV3d7pcd/GE49sXjBgxAk8//TSGDGm5qcOlS5fw9ttvo7HR8ft4IiIiTxMQEIDHH39cFKD68MMPsWPHDhmr8h4RERFQq9Wiec50USooKJB8ja1SqURycrIwbTQaUVhYKHksAMjJyZG8rEqlEk335DWItvtQzlrcvZ97ijvPTVvuPF5EvR3DU+R2tiGIngxPeQuz2YysrCxkZGQgNzeXAakucPe+47FyD3fvZ61Wi/T0dIfP5ebm4oEHHoBWq0VFRYVb6yIiIiLXDR48GCNHjgQAXL9+HSaTSeaKiIiIiIgc+67yjMP5dyeFu7kSMc0Mxx2pHHn2oQkIGhzYg9W4rvqw47vWR4QNZ2BHBp56vrfFrmRERN3jv/4rxS588tsXnsfSh+7Hrl1f2IVxTKbjKP5kO5Y+dL8QnPrrXzc5Pe6sWXdg2bI00bzHHl2GpQ/dj+JPtsNkOm63TuvYv/7VM5g3VyO549VPkubajVP8yXbRazt82NCjXZ3c8Xp/+8LzmDI5DFlZq1FWVupwm4cPG7Bly2bMmyu+aWVi4l12y4aHR9idG+vXrcXSh+5HWVmpaP9ZLBYcPFiBnJzXhG2/+NLLHdbbXTzh+PYVo0aNwlNPPYXAwJbfKY4dO+a1HQqIiKhvag1QTZ48WZj30UcfYfv27TJW5T3S0sTvZ4uKiiSFbfLz8+1uUN+ZhQsXiqZzc3MljWUymaDVap0azzZ4U1lZ2eHyOTk5kkMyOp1ONB0fH9+ttXSVO/dzT3LnudmWu48XUW/G8BSRzAwGAx544AGUlJTYPadWq5GcnIzMzEysWrUK77zzDt555x0UFxfLUClR35KSkoJ33nlHdNeDtvR6PTIzM6HVamEwGNxbHBEREbkkLCxMeFxTUyNjJURERETkTXJfmOFyeKK9MM7xE/XtrqPbc8rh/MBAP7y/7haX6mi1KEGJwtdu73AZy4WrDuff8xOVw/m2NDOGQHP7eKdrc5eCLYfb7T517z2TXA5QvfrrqV0pq8+S+3yXIn7a8C5vg4iIWm6q+px2ld387du3ImXR3ZgyOQwjlYOFPzOmR+HBB5cIQZ5nVzyHpLvmuTT2r5973i6cs337Vjz44BLMmB4lGrft2Bs35gnL267viFodazfvwQeXiF7bLTfPkNTFqivc9XrXr1uLeXM1Drd5y80z8Nijy0TLP7viOcTGxjnc1lP//azdvO3bt2LeXI1o/4WHjcPsO2YKgbp58xYgNfXnndbaHTzl+PYVY8aMwYMPPihM63Q6lJWVyVgRERGRcxwFqP71r39h27ZtMlblHSIiIuxufJ6bmyvc7NxisQjzzWYzSktLkZaWJnQByszMlDxWSEiI3fLtjWWxWFBRUYGcnBw88sgjdo0kOhMXJ34vvHr1apSW/qdTq9lsFnVYKioqwgMPPICsrCyUlpY6vEGswWBAYWEhVq/+T4BfpVIhMTGxW2vpKnfu557kznOzLXcfL6LezE/uAojcyRNDR1lZWaJptVqN1NRUxMTEyFQReQtPPJ97m5CQEGRkZGDJkiXQ6XTYtm2bXRcsvV6PjIwMrFq1CgkJCTJVSkRERFJMnDgR33zzDYCW8NSdd94pc0VERERE5A0iwobjpRVx2LPvJLb9+wT2/XBZ0nqaGUPa7Z5Tc6z98NQWnRl3zT6PiDD7wMZI5UBsffMO/L2oCu9tr5X2AtASIll41wSEjuu8e9SZs5ccdo2aGjUKj98bgjc+aL+L66IEJdIejEZgoOd+/bTvh8vYs+8k7rjVcRjs3nsmQTVuMH7zx0OStrcoQYmH7pvssZ22PJ3c53tbx0/UO1wnYWbH5z0REUkXHR2DnV98jdl3zHRqvWdXPAetg+CVVErlSGS/+hoASO4i1da8eQuE9TsSHR2DZ1c8J3t4xl2v1xnLlqUhLW15u8/Hxsbhrbc32gWuOtJaZ1BQUHeU2ClPOb59SWxsLH744Qfs2rULALBp0yZMmTIFAwcOlLkyIiIiafz9/fH4448jNzcXhw61fNb08ccfw2q1YsGCzsPqfVlKSgpqa2tF3Xr0en2nQZr09HTMnTsX2dnZkseaO3cuLl++jNzcXKfGUqlU0Gq1kseJi4uDWq0WbXflypV2y2VkZIimS0pKHDZnaK+mrKysTt8ju1pLV7hrP/c0d56breQ4XkS9FTtPkdupVOIvJKW2lXSFbavCtqleT6DT6URBDI1Gg6ysLAanusCd55e7x/P087knufu42lIqlUhJSUFeXh6ys7Oh0Wjsllm9erXDuzsQERGR5xg//j93v+fPbSIiIiJyRmCgH+64VYW1K2di45pYPPvQBCxKUNotd9MNA/DQvGC8+uupeP6/Yx2GiK5ebcS2f5/ocLz0l/a32x0pMNAPP/9pNApfux3/89gNDuvQzBiCh+YF4/+emoLC127HLx+5UXKQ5NuDZ9t97t57JuHVX0+1G7P1Nf/ykRuF1/zFbqOjTXiE/33rhw67f8Wpx2Lrm3fg1V9PxUPzgu06jy1KUOLZhyYI+5bBqa6R83xvq/b0JYfzRyoHYuOaWGhm/GebD80L7nJnLCKivio6Ogb7D1Ri2bI0Scu/9fbGLgWnWimVI/H6n97CW29vdGq9t97eiPz3/g6lcqSk5bXaVXh2xXMdLiOlq1NX9eTr3fPNfsnHr3Wbv3/l1U734aJFi1G45WNJ21y2LA3Zr74m+bh0F085vn3J4sWLMW7cOADAxYsX8eGHH8pcERERkXP8/f2Rnp6OKVOmCPO2bt2KrVudD7n3Na03NJdCpVJhzZo1SElJcWmslJQUrFmzxu46xfYkJycjOzsbERERTo2zYsWKDsdo+1xOTo7dNaNSalIq7T8/62ot3cVd+7mnufPcbCXH8SLqjTz31n/Ua6nValFgqLa2VvIP61YGg0HSciqVSpS0PXPmjNvuOiTF7t27RdOLFy+WqZLew53nl7vH8/TzuSe5+7h2JCYmBjExMbj77ruxYcMGUV0lJSVYunRpt4xDRERE3W/s2LHw8fFBc3Mzzpw5g6tXryIwkBc5EhEREZFzQscNEYIZv3zE+fVLvjwmqXtV3l8P4peP3Nju80GDA3HHrSrccavKpTra88YHJtydFN5u96ipUaMwNWpUh2NaLlzF/771Q7vdnTzBspVleH/dLRipdHzX+sBAP+G1Us+T63xva++Bs4hTj3X4XOi4IXj+v2PxfM8MTUTU54SEhOL3r7yKnz/8C1RXf4+vd3+FjRvzhOdffOllRIRH4JaZt3Xr96FBQUFYtGgx5sxJQnV1Ffbu3YM9X38l6s60bFkapk67EVOmRCM2Ns6lcbTaVbjnnmTo9WX4tHiHsP1ly9Iw89bbMGdOUre8ns701OsND48QHb+qqu9F3ZjabjMycpJTx3DWrDtwuOaEw3rnzVuAnyTNhVodi+ho+W5I6ynHt6/w9/fHgw8+iN///vcAgC+//BK33HILwsLCZK6MiIhIutYAVdsOVK3hKXag6lhCQgI2b96MqqoqlJaWirr9qFQqqNVqxMXFIS7OtffubbVup7S0FIcOHUJlZaXoes3k5GSEhYUhNjbW6WsXWymVSuTl5UGn02H37t1CRymVSoX58+cjMTFRWDYiIgJZWVmoqKhAdXU1qqurRR2o1Go1VCoVYmJiMH36dKd/d3Kmlu7kjv3sDu48NwH5jhdRb8PwFLmd7QcY1dXVTndaKi8vl7RcTEyM6AeSwWDwqASybStNqbV1VwikN3Ln+eXu8Tz9fO5J7j6uUsTExODpp59GZmamMK+goIDhKSIiIg/m7++P4OBgnDx5ElarFSdOnOAXrERERETkVt9VnsH6945KWnaLzozgkVUdBplc0V6Hn7b+XlSFn/802uXtv/7Ody6t624/W7GnwwAVuY+c53vbGhbeVe9S1yoiInJNdHQMoqNjsGjRYvz+lVc7Xd5kOi6afvGll10aNygoCLGxcYiNjUNGxpMubaMzra/toYcedmq9s+YL3V5LT73e1tcIoFu6g7VypV5n91tX97Orx5dcM2HCBNx6663CDYrff/99/OY3v4GPj4/MlREREUnXGqB68803UVlZCYABKqmCgoKEEEpGRobT62s0GqeW787AS3sSEhKQkJAArVbb6bKtN3sHIGn5nqyluLi428btif3c1fqcXd/d5ybgvuPVnceayJPwt0hyO9uwR25uLiwWi+T1LRYLtm3bJmnZqKgo0fTmzZslj+PJ+EOpfbGxsaJpV86v3Nxcjxyvt57PUrj7uErlbICLiIiI5BcaGio8NplMMlZCRERERN7ig39VORXAcOTq1Ub85R8H8czvnQsVvfGBCetzD+Cs+VKXxm91/EQ9XlhX2uly722vxQf/qnJ6+1evNmJ97gGU7K93pTxZ/GzFHpTqT3ZpG1evNrq0v0hMrvO9rfc2/9Dlf+9ERNRzKg9WiKYHDx4sUyVE5G7Jycno378/AODEiRPYt2+fzBURERE5z9/fH8uXLxddB7h161YhREXdw/Y6gO7sZkvUFTw3ieTH8BS5XUREBNRqtWheQUGB5PULCgpgNBolLatUKpGcnCxMG41GFBYWSh4LAHJyciQvq1KpRNNms9mp5aVcvFlRUSHqPkRiSqWyy+eXp47n7vPZk7j7uLrKtkYiIiLyPCEhIcLj48ePd7AkEREREVGLNz4wYcHyL/Bd5Rmn1716tRFf7DZiwfIv8N72WpfGL9lfj5+t2IMP/lUFy4WrLm3DUHMef3rnWyxbWYZ9P1yWtM4bH5jwp3e+lTzm8RP1XhecavWbPx7Cy38oc+kYf1d5Bi+sK8UbH/DmDN1BrvO97fjrcw9IGpshKyIi9/vsM/FNRqdMca1TJhF5n0GDBuGee+4Rprdt24bm5mYZKyIiInJNewEqqQ0FqHOnTp0STfMG6eQpeG4Syc9P7gKob0pLSxO1KCwqKkJwcDBSUlI6XC8/P9/p4NDChQtF67R2n+lsLJPJhNdffx16vV5yO0W1Wi0KdlVWViIhIaHd5RMSEkShjoKCgg5bKVZUVCAzM1NSLX2ZO88vd4/nzvPZ07hrP+fk5GDJkiVQKpWdLqvT6UTT8fHxkschIiIiebDzFBERERG5qrVr1OP3hiAyfBiCRw3ESOVA0TJnzZfQcLURNcfqUfH9j9ii6/gGW8544wMT3vjABM2MIbgtbhTCxg/BkKB+CBocKFrOcuEq6i0NqD19CZU//OhyaAsAtujM2KL7st3XfNZ8CbVnLkG355TD15r48Ocuj92VdV1Rsr8eJfvFx3jokECEjhsiWu6s+RLqLVfx7cGzTgemeuI1ubpNT6rFETnO91Yl++tR8mTLeX9j9EiMGjlQNO7xE/WoOVaPbf8+0eWxiIhIurKyUmzcmCeaFxk5SaZqiEgOt99+O4qLi1FXV4fTp0+jrKyM39ETEZFXag1Qvfnmm6isrAQAfPzxxwCA+fPny1lar/D55+LPqNoG1YjkxHOTSH4MT5EsIiIikJ6eLgQ/gJYQyN69e5GamgqVSiW0IzSbzThy5AjefPNNIZiUmZmJ7OxsSWOFhITYLd/eWBaLBUajETqdzqUQTVxcnGi91atXY82aNYiLixNey6ZNm4QAiEajEYWnSkpKAACLFy9GRESEMN9gMGD37t3CsqmpqW7rpOONXDm/PvjgA+j1egCwW9eTxnPn+exp3LWfi4qKUFRUBI1Ggzlz5mDMmDGiDhVAy7/J8vJy0fZUKhUSExO746USERFRDxo3bpzw+OTJk2huboaPD5syExEREZF0LYEZ+YL4LSEf93Z3kvs1u1tfe72eTI7zvdUbH5gAdhQjIvIIZvNZ/PEP60XzXnzpZeG7QSLqG/z8/JCUlIRNmzYBaOk+FRsby8/4iYjIKzFA1TNMJpNwHS7Q0hBByk3UiXoaz00iz8DwFMkmJSUFtbW1olCHXq8Xgg7tSU9Px9y5cyWHpwBg7ty5uHz5sijoIGUslUrVYScoW3FxcVCr1aLtrly50m651vBUSEiIXaCjpKRE9APSlkajwdKlSxme6oSr55dGo0FKSopT4Sl3j+eu89kTuXM/d/ZvsS2VSoWsrCx+QUNEROQFBg4ciOHDh+P8+fO4fv06Tp8+jTFjxshdFhERERERERERUa+39KH78ehjj+PGG2dI/l7t8GEDXvzdKmzfvlU0f+HC5B6okIg83W233YYdO3bAYrHgzJkz2L9/P2666Sa5yyIiInIJA1Td73e/+51oOjU1VZ5CiGzw3CTyDLz1BskqIyMDq1atkrSsSqXCmjVrkJKS4tJYKSkpWLNmDVQqlaTlk5OTkZ2dLeoAJcWKFSs6HMP2uZSUFGRmZkradmpqqteHX9zJmfMLAFatWtWl/evO8dx1Pnuint7POTk5UKvVkpdv3be8CwAREZH3aNtV8vjx4zJWQkRERERERERE1Hds374VKYvuRnjYOLz33rsoKyuFyWT/+ZzJdBxlZaXIylqNW26eYReceuvtjQgJCXVX2UTkQfz9/ZGYmChMf/HFFzJWQ0RE1HWtAaqoqChh3scff4ytW7fCarXKWJm80tLSoNPpJC9vMpmg1WphNBqFeRqNBjExMT1RHvVhPDeJvBs7T5HsEhISsHnzZlRVVaG0tFTUUUalUkGtViMuLg5xcXFdHqt1O6WlpTh06BAqKytFHWuSk5MRFhaG2NhYl4MQSqUSeXl50Ol02L17t9C5RqVSYf78+aIPcVrNnTsXt956K3bv3o0DBw6Iut1oNBpERkYiISGB4QwXSD2/Jk2a1C1dg9w5njvOZ0/Vk/s5IiICWVlZqKioQHV1Naqrq+3apapUKsTExGD69OnsNkVEROSFQkNDUV5eDqDlg6r4+HiZKyIiIiIiIiIiIupbMp950qX1nl3xHBYtWtzN1RCRN7n99tuxdetWXL16FQaDASdPnsTYsWPlLouIiMhljjpQbd26FXV1dbj//vvh6+src4XuZzQasXr1agAtTQfUajWCg4NF10GazWbU1tZCr9ejoKBAtL5KpUJaWppba6a+gecmkXdTWPtyNJm8WlJSkvBYo9GwIxMREREREUlSXl6O3NxcAMDkyZPx1FNPyVwRERERkfskPvy53CUQERHhs3fnyF0CkSzM5y7KXYKslj50v10XKWdkv/oaHnro4e4riIh6lHLEoB7b9vvvv49du3YBAGbNmoWf/exnPTYWERGRu1y/fl0UoAKAqKgopKWloV+/fjJW5n5paWmiTj3O0Gg0SEtL63U3nCfPwHOTyLv5yF0AkStMJpNomp1fiIiIiIhIqpCQEOHx8ePHwXuKEBERERERERER9bzX//QW3np7o9PrPbviOez5Zj+DU0QkmDVrlvD4m2++wZUrV2SshoiIqHv4+/sjPT0dt9xyizCvsrIS2dnZqK+vl7Ey98vOzkZ6erpT66hUKqxatQparZbhFOoxPDeJvJuf3AUQueLUqVOi6ZiYGJkqISIiIiIibzNs2DAMGDAAly9fxqVLl1BfX4+hQ4fKXRYREREREREREVGvFhQUhEWLFmPRosU4eLACen0ZTpwwYf26taLlnl3xHIKChmDq1GmYMiUKSuVImSomIk8VEhKCiRMn4siRI7h27RrKyspEgSoiIiJv5efnh4ceeghKpRIff/wxgJZmA6+88goeffRRjB8/XuYK3SMoKAgpKSlITExEVVUVDh06hMrKSuj1emEZlUoFtVqNsLAwREREICIiQsaKqa/guUnk3RieIq/0+eefi6ajoqJkqoSIiIiIiLyNQqFASEgIqqurAbR0n2J4ioiIiIiIiIiIyH2io2MQHd1yk1StdpXM1RCRN5o1axaOHDkCANi7dy/DU0RE1GsoFArMnz8fw4cPR0FBAZqbm3H+/HmsW7cOKSkpmD17NhQKhdxlukVQUBDi4uIQFxcndylEIjw3ibyTj9wFEDnLZDKhpKREmFar1WxjSERERERETgkJCREem0wmGSshIiIiIiIiIiIiIiJnzZgxA/7+/gCAw4cP49y5czJXRERE1L1uueUWPPnkk+jfvz8AoKmpCf/85z/x1ltv4fLlyzJXR0RE5H0YniKv87vf/U40nZqaKk8hRERERETktUJDQ4XHDE8REREREREREREREXmXwMBA3HjjjcJ0aWmpjNUQERH1jEmTJuH555/HhAkThHnffvstXn75ZaEDIxEREUnD8BTJJi0tDTqdTvLyJpMJWq0WRqNRmKfRaBATE9MT5RERERERUS82btw44THDU0RERERERERERERE3icuLk54vHfvXlitVhmrISIi6hkjRozAs88+i5/85CfCvPPnz2PdunV4//33cfHiRRmrIyIi8h5+chdAfZfRaMTq1asBtHSPUqvVCA4OhlKpFJYxm82ora2FXq9HQUGBaH2VSoW0tDS31kxERERERL1DcHAwfH190dTUBLPZjKtXryIwMFDusoiIiIiIiIiIiIiISKIpU6ZgwIABuHz5Mmpra2EymRAaGip3WURERN3O19cXixYtQmRkJP7yl7/g4sWLsFqt2LVrF/bt24e7774bCQkJ8PFhTw0iIqL2MDxFslGpVEIXqYKCArtwVEc0Gg3S0tJEQSsiIiIiIiKp/Pz8MGbMGJhMJlitVpw4cQJhYWFyl0VERERERERERERERBL5+flBrVbjyy+/BAB89913DE8REVGvFh0djeeffx5///vfUV5eDgC4fPkyNm3ahC+//BL33nsvJk+eDIVCIXOlREREnocRY5JNdnY20tPTnVpHpVJh1apV0Gq1DE4REREREVGXjBs3TnhsMplkrISIiIiIiIiIiIiIiFwxbdo04XFFRYWMlRAREbnH0KFDkZ6ejieffBLBwcHC/JMnT+K1117DmjVrsGvXLjQ0NMhYJRERkedh5ymSTVBQEFJSUpCYmIiqqiocOnQIlZWV0Ov1wjIqlQpqtRphYWGIiIhARESEjBUTEREREVFvEhoaim+++QYAcOLECZmrISIiIiIiIiIiIiIiZ02aNAn+/v64fv06jh07BovFgqCgILnLIiIi6nFTpkzBypUrodPp8PHHH+PKlSsAWkJU77//PrZs2YL4+HgkJCRg7NixMldLREQkP4anSHZBQUGIi4tDXFyc3KUQEREREVEfws5TRERERERERERERETezd/fH5MmTUJFRQWsVisqKytxyy23yF0WERGRW/j6+uLOO+9EXFwctm/fjq+//lroONXQ0ACdTgedToexY8ciOjoa0dHRmDhxIvz9/WWunIiIyP0YniIiIiIiIvIASUlJouni4mKZKuk7QkJChMcnTpxAc3MzfHx8ZKyIiIiIiIiIiIiIiIicFRMTg4qKCgDAd999x/AUERH1OYMGDcJ9992HhQsXYu/evdDpdDhx4oTw/MmTJ3Hy5El8+umn8PHxwdixY6FSqRAcHIwRI0Zg+PDhCAoKgr+/PwICAuDv7w+FQiHjKyIiIup+DE8RERERERFRnzRw4EAMHToUdXV1uHbtGsxmM0aNGiV3WURERERERERERERE5ITo6Gjh8aFDh9DY2Ag/P14WR0REfU9gYCBmzZqF22+/HUeOHIFOp4Ner0djY6OwTHNzM0wmE0wmU7vb8fX1RVNTkztKJiJq14IFC7BgwQK5y6BehL8lEhERERERUZ8VEhKCuro6AIDJZGJ4ioiIiIiIiIiIiIjIy4wYMQJjxozBqVOn0NDQgMOHD2PSpElyl0VERCQbhUKBsLAwhIWF4YEHHkBVVRUOHjyI77//HmfOnOl0fQaniIioN2J4ioiIiIiIiPqskJAQVFRUAGgJT6nVapkrIiIiIiIiIiIiIiIiZ0VHR+PUqVMAgIqKCoaniIiI/r+AgABMnToVU6dOBQBcuXIFx48fx/Hjx3Hu3DmcP38e58+fx+XLl3Ht2jVcu3YNzc3Nom5VREREvQHDU0RERETUI8xmM8rKyrBz505kZWXJXQ51Ax5T6o1CQkKExyaTScZKiIiIiIiIiIiIiIjIVTExMfjss88AAN999x3uvfdemSsiIiLyTP3790dkZCQiIyPlLoWIiMitGJ4iIiIiom6n1Wqh1+vlLoO6EY8p9VYMTxEREREREREREREReb/w8HD069cPDQ0NOHPmDM6cOYNRo0bJXRYRERERERF5CB+5CyAiIiKi3ochm96Hx5R6q5EjRyIgIAAAUFdXh0uXLslcEREREREREREREREROcvX1xdTpkwRpisqKmSshoiIiIiIiDwNw1NERERERETUZykUCowbN06YZvcpIiIiIiIiIiIiIiLvFBMTIzyurq6WsRIiIiIiIiLyNAxPERERERERUZ8WEhIiPD5x4oSMlRARERERERERUW+mUCjkLoGIyC3k+v8uMjJSeHz48GFYrVZZ6iAiIiIiIiLP4yd3ASSvrVu3YuvWrXKXQURE3cTPzw8KhQIBAQEICAjAwIEDMWzYMIwYMQIjRoxAaGgoQkND0b9/f7lLJSIi8hhtw1PsPEVERERERERERD1FoQB4HT8R9QU+MoWnhg8fjqFDh6Kurg6XLl1CbW0txowZI0stRERERERE5FkYniIiIupFGhsbAQDXr1/HpUuX8OOPPzq8CHzUqFGYPHkyoqOjMWnSJAQEBLi7VCIiIo/B8BQREREREREREbmDj48Czc1MTxFR76fwkWlchQIREREoKysDABgMBoaniIiIiIiICADDU0RERL2Kr68vmpqaOl3uzJkzOHPmDHQ6Hfz8/DBjxgwkJCQgLCwMCpnuAkYds1gsqKqqQmlpKfR6PYxGIwBApVJBrVYjISEBMTExTm/XbDajrKwMNTU1KCoqEuZrNBpERkYiPj5eFCpoT1JSkkvPFxcXt7tM2+ekkLp+Z8uVlpaitLRUtD/UajXi4+Ml7w9nx7I9pgkJCVCr1V57TLVaLfR6vTBv8+bNCAoK6nB7FosFixcvFs1zZT21Wo2srKwO1wGAiooKVFdXo7q6GiUlJcL81n9TYWFhiI2NhVKp7HRbbXV0zHU6HbZt2wa9Xg+VSoWnn37apWPc9jVkZmaK5qWnpyMlJcXlbfZV48aNg0KhgNVqxalTp9DY2Ag/P/66TERERERERERE3cvX1weNjc1yl0FE1ON8fWVKTwGi8NQPP/yAWbNmyVYLEREREREReQ5eDdbHLViwAAsWLJC7DCIi6iZWqxWNjY24du0arl27BovFgvPnz+PcuXOora2F0WjEyZMn0dz8ny/mGhsbhQDHuHHjkJCQgPj4eAQGBsr4SqitwsJC5ObmOnzOaDTCaDSiqKgIKpUKWq0WERERkrabn5+PgoICh8+VlJSgpKQEubm5SE5OxpIlS5wOkXib0tJSvPnmm0KIqS29Xg+9Xi/sj9TU1E5DPR3R6XTIz893OJbRaERBQQEKCgqg0WiQkZEheSxPOaazZ88WhaeMRmOnIaH29oWz682ePbvD5Tva963ba/tcd+wrs9kMrVYr2q7RaERmZqbTIcG227QNTiUnJzM45aKAgACMHDkSZ86cQVNTE06fPo1x48bJXZYdq9WK69ebcL2xCY3Xm9FstaK52QqrlXcrJiJSKBTw8VFAoVDA388H/v6+8Pf35c0hiGy0/TyAiIiIiNzP388XV682yl0GEVGP8/fzlW3s8PBw4bHBYIDVauVnRERERERERMTwFBERUW+iUCjg7+8Pf39/DBw4EMOGDcP48eNFy1y/fh1Hjx7FwYMHcfDgQZw4cUJ47sSJE3j//fexZcsWzJw5E/PmzcOgQYPc/TLo/3MUuOiI0WhERkZGp2EMZ7dbVFQEvV6PrKysXhug6iigZqur+8OZsUpKSlBXV9dpJyVPO6a2AT69Xt9pCKq6utrhPGfXay88aLFYkJOTI+oyJUVRURGKioqQnZ3tcpeodevWST42UlgsFmi1WtG81qAduS4kJARnzpwBAJhMJo8KTzVbrWi4ch1XGq4zKEVE1A6r1Yqmppb/Ixsbm3Cl4ToUCiAwwB/9+vvDT8a7HRN5guvXr2PPnj34/PPPAfCO20RERERy8ZMxTEBE5E5y/n83duxY9O/fH1euXEFdXR3Onz+PESNGyFYPEREREREReQaGp4iIiPoYf39/3HDDDbjhhhuQnJyMU6dOQafT4ZtvvkFDQwMAoKGhAf/+97+xZ88eLFiwAHfccQd8ffmFnrvZhmGSk5ORlJQkCodYLBacOXMG5eXlkgI5raGLtttVq9VITU0VBUMqKipQUFAgdA8yGo3QarXIy8tzuF3bwFZSUlKHz3sSnU4n7LvWfaFSqYRuTyaTCXv37hXtX6PRiLy8PLsAS2d27NghbMfR8TQYDCguLkZRUZEwT6/Xo7CwsN2OQp54TCMiIqBSqYSadDodli5d2u7yALBt2zaH8zrrpLR3717hsUqlajc8lZmZaRdgSk9PR3x8PEJCQoR5ZrMZR44cwQcffCDqnpWZmelSgEqn00Gv10OlUmH58uWIi4sTxtm0aZNT22qVk5Mjei0qlYrBqW4QEhIiHHOTyYSbb75Z5opaXL/eBMuFBoamiIhcYLUCDVevo+HqdfTv548BAwLBmwxTX3Pp0iV88cUX2LlzJy5evCh3OURERER9np+fD/x8fdDYxI6gRNR7+fn5wM9PvhvZKBQKhIeHo6KiAkDL928MTxERERERERFvuUpERNTHjRkzBj/96U/x8ssv42c/+xnGjh0rPHflyhVs3rwZa9aswaFDh2Sssu/ZsWOHKByRnp6OjIwMu2BIUFAQIiIikJKSgs2bNyM1NbXD7dqGLtLT05GVlWUXCImJiUFWVhY0Go0wz2g0orCwsCsvyyOtXr0agHhftAangJZARUpKCrKzs0XrlZSUQKfTOTVW6zays7MdHs+IiAhkZGQgPT1dND83NxcWi8XhNj31mCYkJIjGMZvN7S5rNpsddmbqbD2LxSIKOLUds62srCzR9jUaDf72t78hJSVFFJwCAKVSibi4OGRlZdkdhw0bNrR7HNqTn58PlUqFrKwsITjVOo4rgafCwkK77llZWVmic5Zc0/ZcMJlMMlbyHw0N11FvucLgFBFRN7jScB319ZfR3Mz/U6lvOHfuHDZt2oSVK1fi448/ZnCKiIiIyIP07x8gdwlERD2qfz/5/58LDw8XHhsMBhkrISIiIiIiIk/B8BQREREBAPr164dZs2Zh5cqVeOqpp0QhqtraWrz22mvIzc1FXV2dfEX2ITt37hRNJyYmdrpOUFBQh919SktLRaGL5OTkTrv6aLVaqFQqYbqjEI83S01N7XRfxMTEYM2aNaJ5+fn5To+1atWqTrsXpaSkiPY7AFRVVdkt58nHVK1Wi6aPHDnS7rK2z7Vdt6P1bANXtmMCLZ2f2u4jlUoFrVYLpVLZ7nZbpaSkIDk5WTTeZ5991ul6tjUuX75c0nidKS0tteswl52d3S3bJnF46sSJE7IHlq5fb8LFS1dlrYGIqLdpbGqG5QJDqdS7HTt2DH/+85/xwgsvYOfOnbh27Zrw3PDhw3HffffJWB0RERERAUBgoB98fXmpBhH1Tr6+PggM9JO7DNENDA8fPixjJUREREREROQp+IkcERERiSgUCkyePBnPP/88lixZggEDBgjPlZeX4+WXX8bBgwdlrLBvaNtNB0C3dJX54IMPRNOddalqtXjxYtG0oxCPN1OpVB2GztqKi4sTBXSMRqNTd6tTq9XtdkeyZbvfS0tL7Zbx5GNqG/7qqHtd2+dUKhXmz58vab3q6uoOxwTsA25arbbd7Tliu0+dDZup1WpRxylXmUwmrFy5UjQvMzOz0yAeSTdkyBAMHDgQAHDx4kXU19fLVkuz1QrLhQbZxici6s0aG5tx4SLDqdS7WK1WHDx4EBs2bMDatWuxb98+UUgwJCQEy5Ytw4svvog777xTxkqJiIiIqFXQ4H5QKOSugoioeykULf+/eYLx48fDz68lxFVbW4sLFy7IXBERERERERHJjeEpIiIicsjHxwezZ8/G7373OyQkJEDx/7/Fu3jxIv70pz9hy5YtaGpqkrnKvsNkMnVpfYPBIApkpaenSw5k2YYzOgqzeCPbIFFnZs+eLZouLy+XvO69994reVnb/W7bZcnTj2lQUBA0Go0wXVBQ0O6yOp1OeDx//nxR57u2z9nau3ev8Fij0di9foPBINpvGo1GdKdBKYKCguwCVM6EzWzPF1eYzWb87ne/E81LTU3F3Llzu7xt+g+FQiHqPtXV/3e7ouHKdXZFISLqQdeuNeL6df4uQ96vsbERe/bswZo1a/CnP/3J7uYCU6ZMwVNPPYXf/OY3iIuLg6+vr0yVEhEREZEtX18fDB7EABUR9R4KBTB4UD+P6azn5+eHCRMmCNPsPkVERERERESe8RsrEREReaxBgwbh/vvvx4oVKzB8+HBh/qeffor169fj3LlzMlbXe7UNnQAtwRNnut3Ysu2ONG3aNMnrtg0TAMDJkyddrsMTOdu5x3b52tpayetOnDhR8rK2+922G5k3HNPp06eLph2FUcxmsyjgFBkZKQo4GY1Gh+tZLBbRPrEdC7DfR3PmzJFaukjbbmOAc2Gz7ugMlZeXZxcCk9otjZwzbtw44bFc4Smr1YorDddlGZuIqC+5dJndp8h7XblyBZ9++ileeOEF5Ofni97P+/j4ID4+Hs8//zyefPJJTJ48WbgZChERERF5loAAPwwJ6g8fH75fIyLv5uOjwJCg/ggI8JO7FJG23zfZfmdEREREREREfQ/DU0RERCTJxIkT8fzzz+PGG28U5h09ehQvv/yyU11YSJq7775bNF1SUoLMzMwOu/B0pKamRjTtbPcd21p6E9sgkbPLFxUVSV5XqVQ6NVZHvOGYxsbGiqZtawaAyspK0bRKpQIgDhA6Ws+2E5ftWI7WGzNmTCcVOzZ06FDRtDNhM6ndwNqTn58vOj4qlQparbZL26T2hYaGCo+PHDkiSw3Xrzex6xQRkRs0NjajqalZ7jKInFJXV4fCwkKsXLkSW7ZsQV1dnfBcYGAgNBoNXnrpJTz88MNO/55DRERERPLw8/PFsKEDMGBAAEPvROR1FAoFBg4IwLChA+Dn53ndjsPDw4XHDE8RERERERGRZ93yg4iIiDzagAED8Nhjj2Hnzp0oLCxEU1MTrly5gtdeew2pqam45ZZb5C6x14iJiYFGoxGFJoxGI1avXg0ASE9PR0JCguQwjm3AJykpqdtqJXl4wzFVKpVQqVRC0KmiogIJCQmiZSoqKoTHGo1GCBtNnz5dOP8drVddXS08VqlUDv8t2O4jVy8gtV2vpKREcoCpK+EpnU6HgoICYVqlUiErK8vl7VHn2n6RWlNTA6vV6vaLVq43Nrl1PCKivuzatUb07x8gdxlEnTpx4gQ+//xzlJaWoqlJ/F4hKCgId955J2bNmoUBAwbIVCERERERdYVCocCA/gHo388f1xubcf16Exobm9DcbEVzs5U32iEij6BQKODj0/LHz88X/v6+8Pfz8ejgZ1hYGBQKBaxWK44fP46Ghgb069dP7rKIiIiIiIhIJgxPERERkVMUCgXuvPNOhIWF4a233sKPP/6I5uZm5Ofn4/z585g3b55Hf0juTbRaLSIjI5Gbm2v3XG5uLnJzc6FWq5GamoqYmBgZKiTq3Pz584VzuKioCBkZGaLn2wacpk+fLjxue047Wm/v3r2iMXqj1rBkq6VLl3Zr9zKyN2LECAwZMgT19fW4dOkSTp8+jeDgYLfW0HidXVCIiNzl2vUm9O8vdxVEjlmtVhw8eBCff/65w27PwcHBSExMRHx8PPz8+DE/ERERUW+gUCgQ4O+LAH/P695CROSN+vfvj3HjxsFkMsFqteLIkSOYMmWK3GURERERERGRTHzkLoCIiIi80/jx4/HrX/9a1JHl448/xnvvvYfGxkYZK+tdUlJS8M477yA5Odnh83q9HpmZmdBqtTAYDO4tjkiCyMhI0XTb89RkMomeaxuYsu321HZZi8UCvV7f7hi9hUajEU3n5+fDbDbLVE3foFAoRN2nDh8+7PYamnknYSIit2lu5v+55HmuXbuGXbt24aWXXkJOTo5dcCo8PByPP/44/ud//ge33norg1NEREREREREHYiIiBAe//DDDzJWQkRERERERHLjN6tERETksiFDhiAzMxN5eXmorKwEAOzZswcWiwXLly+Hv7+/zBX2DiEhIcjIyMCSJUug0+mwbds2GI1G0TJ6vR4ZGRlYtWoVEhISOt1mcXFxT5Xb61ksFtG0SqWSqRIxTz2mtl3RDAaD8EVVTU2NMF+lUtkFppKTk4XOVBUVFcLztud/b+28lpaWBoPBILxeo9GIdevWISsrS+bKerfw8HAhnHf48GHcdtttbh2fF/ITEbmPlYFV8iD19fXYuXMnvvzyS1y6dEn0nEKhwIwZMzBnzhxMnDhRpgqJiIiIiIiIvE94eDh27twJALwRJRERERERUR/HzlNERETUJf369cPjjz+OW2+9VZhXWVmJN998E9evX5exst5HqVQiJSUFeXl5yM7OtutKAwCrV6+26+YDAGq1WjRtGwAi6Wz3ne2+dRdvOqZtz9UDBw4Ij3fv3i08dhT6axuKartedXW1w213NC5g3+lKKtv12usE192USiW0Wq1onl6vZ3iqh7W9C2XbgJ+78EJ+IiL3YWCVPMHx48fx7rvvYtWqVfjkk09Ewal+/fphzpw5eOmll5CWlsbgFBEREREREZGT2n7mf/ToUTQ2NspYDREREREREcmJ4SkiIiLqMl9fXzz44INYsGCBMI8Bqp4VExMDrVaL7Oxsu85HJSUldsvbLnPmzJkerc/d3Bkcsg1ThIWFuW3strzpmM6ZM0d43Pb8bPvYUQit7b5tu+zevXsdbtvW2LFjRdOnTp2SWLFYXV2daDo4ONil7bgiIiICmZmZonklJSUoLCx0Ww19zbhx4xAYGAig5d/VhQsXZK6IiIiIepvm5maUl5cjOzsb//d//4e9e/eiqalJeH7EiBG477778PLLL+Pee+/FiBEjZKyWiIiIiIiIyHsNGTIESqUSANDY2Ihjx47JXBERERERERHJheEpIiIi6hYKhQILFizA3XffLcxjgKrnxcTE4OmnnxbNKygocLhcWwaDoSfLcklXugQZjUaXx3V2X7TtlgSI71jnTt5wTFvZ3iG/oqLCrl7bMBgAhISEiOYbDAZYLBbo9fp2t92WbSCrtLTUqbpbtR0PAKZNm+bSdlw1d+5cu38fubm5DFD1EB8fH1FwT47uU0RERNQ7Xb16FTt37sSLL76I3Nxcu/fE4eHheOyxx/Diiy/izjvvRL9+/WSqlIiIiIiIiKj3aPtdnid/n0ZEREREREQ9i+EpIiIi6lbz589ngMrNbEM0jkRFRYmmN2/e3FPluMy2S1BFRYXkdXU6ncvjFhcXS17WZDKJOiCpVCrZwlPecExbKZVKUZCpurpa9OWURqNBUFCQw3UTEhKExwaDQRSUU6vVwt0CHbH9t1FUVORUKA9o6WrWNpAo1zHXarV2AbPc3Fyn/p2QdOHh4cLjw4cPy1gJERER9QY//vgjtmzZgueffx6bNm3C2bNnhed8fHwQGxuLX//613j22Wcxffp0+PjwY3siIiIiIiKi7sLP/ImIiIiIiAhgeIqIiIh6wPz587FgwQJhmgEq97LttgO0hFeSk5OFaaPR6HTXmpycHMnL2oY8zGZzp+tMmTJFNC01DFRaWoqioiLJtdkqKiqSHECx7eq1dOlSl8ftKm84pm3Fx8cLj6urq0XdfKZPn97uem3Pi5qaGlRXVzvcZnsyMzNF06+//rqUcgW2x3z58uVOrd+dfve739nNy8zM5F0Se0DbL1LZeYqIiIhcdfToUfz5z3/G//zP/+DTTz/FlStXhOf69++Pn/zkJ/jf//1fPPLII5gwYYJ8hRIRERERERH1Yradp5qbm2WshoiIiIiIiOTC8BQRERH1iAULFjBA1QU5OTmSwym2XZfaC5QsXLhQNJ2bmyspbGMymaDVap0KKNkGuCorKztdZ9KkSaJpo9GI/Pz8DtepqKjAypUrJdfVng0bNnQaQMnPzxd1nVKr1aKuSHLw9GPa1rRp04THJSUlorE76uQ0ceJE4XFRURFqa2sdbrM9c+fOFdWu1+uRlZUl6d9XYWGhqE6NRoO4uLhO1+spISEhWLVqld18qa+HpJs4caLQ8cFoNPJnFxEREUnW3NyM/fv3Y926dfj973+Pffv2iS7KGjlyJJYsWYKXX34ZixYtwrBhw2SsloiIiIiIiKj3GzVqFAYNGgQAaGhowMmTJ2WuiIiIiIiIiOTA8BQRERH1GAaoXFdUVIQHHngAWVlZKC0thclkslvGYDCgsLAQq1evFuapVCokJiY63GZISIhdF57c3FxotVpUVFTAYrEI8y0WCyoqKpCTk4NHHnkEer3eqfptAyarV69GaWmpMG02m+26HgUFBdnVV1BQgKysLLvOUCaTCYWFhcLyqampTtXXlkqlgtFoREZGBgoLC0X7unU/aLVauw5ETzzxhMtjdhdPP6ZtdRSQ6ug5pVIp6nolNXTV1ooVK0TbKCkpwQMPPGB3vIGW11FaWgqtVovc3FxhvkqlglarlTReT0pISLA7341Go0fU1psEBAQgNDQUANDY2Aij0ShzRUREROTprly5gpKSErzwwgt4++237bpX3nDDDUhPT8dvf/tbzJ49G4GBgTJVSkRERERERNS3KBQKu+5TRERERERE1Pf4yV0AERER9W6t4amtW7cC+E+Aavny5fD395ezNK9QUlIi6nbUEZVKhaysLAQFBbW7zNy5c3H58mVRKESv13capHE2OBIXFwe1Wi3arqMOURkZGXb1HThwQPSaO9sHGo0GS5cutQs3SZWVlQWtVguj0Yjc3FzRvmlPdnY2QkJCXBqvu3n6MW0rNTXV7jhJCb7Nnz/f7rg4E5hTKpWi49xK6vHWaDQeFU5aunQpKisrRcfCaDQKr5G6R3h4OI4dOwYA+OGHHxAeHi5zRUREROSJjh07hl27dqG0tNTuRiE+Pj6IjY3FnDlzhGA2EREREREREblfREQEDhw4AKAlPDV79mxZ6yEiIiIiIiL3Y+cpIiIi6nHsQOW8nJwcqNVqycsnJycjOzsbSqWy02VTUlKwZs0aUSceKduW2uWnlW23H1vtPafVapGcnCxpjNTU1C6HRVqDNVL2t1qtxjvvvIOYmJgujdndPP2YtpoyZYqkebYiIyNdWq8tpVKJvLw8pKenS15HpVJh1apVHhlIcnQsSkpKkJ+fL1NFvU/bfx+VlZUyVkJERESe5tq1a9i9ezfWrl2LtWvXYvfu3aLfbwcMGIC77roLq1evxsMPP8zgFBEREREREZHMbrjhBuGxwWCA1WqVsRoiIiIiIiKSAztPERERkVs46kCVm5uL9PR0dqByICIiAllZWaioqEB1dTWqq6tF3ZfUajVUKhViYmIwffr0DrtNORIXF4e4uDiUlpbi0KFDdl1skpOTERYWhtjYWEmBLEdawyo6nQ67d+8W6lepVJg/fz4SExPbXTcjIwMLFy7E3r177V67RqNBZGQk4uPju637U2uAqqKiAjqdDnq9XuhQpFarERUVBbVa7XGhqbY8/ZgCwKRJkyTNs+UolCVlPUdSUlKQmJiIqqoqlJaWwmg0ivaTRqPB2LFjPf54K5VKPP3008jMzBTNLygowKBBg5CSkiJTZb3HpEmT4OPjg+bmZtTU1ODKlSvo37+/3GURERGRjGpra7Fr1y7s2bMHV65csXt+7NixSEhIwC233IKAgAAZKiQiIiIiIiIiR8aNG4d+/fqhoaEBFosFZ8+exahRo+Qui4iIiIiIiNxIYeWtNIiIiMiNtm7dKgSogJbuMQxQkTslJSWJpouLi2WqhIg83YYNG1BdXQ0AeOyxxzB9+vQeH9N87mKPj0FERP+hHDFI7hLIwzU1NeHbb7+FTqcT3he05efnB7VajVmzZiEsLAwKhUKGKp2T+PDncpdARESEz96dI3cJRERE1Me8/vrrqKysBACkpqbi1ltvlbkiIiIiIiIicid2niIiIiK3su1AdejQIXagIiIijxQTEyNcJF1ZWemW8BQRERF5hh9//BFffvklvvrqK1gsFrvnR44cidtvvx0zZ87EoEHeFcJTKADeUo2IiOTkBVljIiIi6oVuuOEGITxlMBgYniIiIiIiIupjGJ4iIiIit1uwYAEUCgU+/vhjAC0BqjfeeAPp6ekICAiQuToiIqIWMTExKCwsBNASnrJarV7RTYKIiIhcY7VacejQIeh0Onz33Xew2iSMfHx8MHXqVCQkJGDy5Mle+75g8EB/WC5el7sMIiLqw4IG8SZaRERE5H4RERHCY4PBIGMlREREREREJAeGp4iIiEgW8+fPh4+PDz766CMAwPfff4833ngDjz/+OANURETkEUaPHo0RI0bg3LlzOH/+PE6ePIlx48bJXRYRERF1s4sXL+Lrr7/Grl27YDab7Z4fMmQIbr/9dtx2220YOnSo+wvsZkMGMTxFRETyChrEz3+JiIjI/caPHw9/f39cv34dZrMZ9fX1GDJkiNxlERERERERkZswPEVERESymTt3LhQKBT788EMAQFVVFQNURETkMRQKBaZOnYqdO3cCAPbt28fwFBERUS9htVpRU1ODXbt2Qa/Xo7Gx0W6ZKVOmYNasWZg2bRp8fHxkqLJnDAkKwPHay3KXQUREfdjQwew8RURERO7n5+eHiRMnorq6GkBL96mbbrpJ5qqIiIiIiIjIXRieIiIiIlndddddUCgUKCoqAsAAFREReRa1Wi2Ep/R6Pe655x4oFAp5iyIiIiKXNTQ0YO/evdDpdDh58qTd8wMHDsTMmTMxa9YsjBw5UoYKe55qzEBUVNfJXQYREfVhoWMGyl0CERER9VERERFCeOqHH35geMpFFosFu3fvxoEDB1BSUgIA0Gg0SE1NRUhIiMzVeaakpCTRdHFxseR1ub/JGV0514iIiIh6O4aniIiISHZJSUlQKBTYsmULgJYAVU5ODpYvX47+/fvLXB0REfVl4eHhGDJkCOrr63HmzBmcOHGCX0QRERF5GavVisOHD+Prr7+GXq/H1atX7ZYJCwtDQkICZsyYAX//3t0NY9qkodj2xQm5yyAioj5s6qShcpdAREREfVRERITw2GAwyFiJ96qoqMCGDRtgNBpF80tKSlBSUsKgRjfj/iYiIiIi6j4MTxEREZFH+MlPfgKFQoHCwkIAQHV1NdavX4+MjAwMHz5c5uqIiKivUigUuOmmm4Q7+e3bt4/hKSIiIi9x7tw57NmzB3v27MG5c+fsng8MDMTNN9+MWbNmYdy4cTJUKI9pvGCdiIhkNvWGIXKXQERERH1UWFgYfHx80NzcjFOnTuHSpUsYOJBdMaWqqKhAZmam3GX0GdzfRERERETdi+EpIiIi8hiJiYnw8fHB5s2bAQAnT57EK6+8goyMDISGhspcHRER9VWxsdPuHQgAAK2wSURBVLGi8NTChQuhUChkroqIiIgcaWhowP79+7Fnzx788MMPDpcJCQnBrFmzEBcXh379+rm5QvmNGtEPoWMG4vipS3KXQkREfdC40f0xWtlf7jKIiIiojwoICIBKpcLRo0eFTtXTpk2TuyyvYLFYsGHDBtG89PR0JCYmIigoCBaLBQUFBfIU1wtxfxMRERERdT+Gp4iIiMijaDQaBAUFIT8/H42Njaivr8f69evxi1/8AlOnTpW7PCIi6oPGjx+PESNG4Ny5czCbzfjhhx8QGRkpd1lERET0/1mtVlRXV2PPnj3Yv38/rl27ZrfMwIEDERcXh5kzZyIkJKTPB6GTE0Pw2ntVcpdBRER90D13hqCP/xgmIiIimU2aNAlHjx4FABw6dIjhKYl2794No9EoTKempiIlJUWYDgoKQkZGhhyl9Urc30RERERE3Y/hKSIiIvI4sbGxGDp0KN58801cunQJ165dQ25uLhYtWoQ5c+b0+YvciIjIvRQKBeLj47F9+3YAwK5duxieIiIi8gCnTp1CaWkp9u7di/Pnz9s97+Pjg+joaMycORMxMTHw8+PH4a2SbhuDjR8cxsXLjXKXQkREfUhggC/umjVW7jKIiIioj5syZQo++eQTAEBlZaXM1XiPmpoa0fStt94qUyV9A/c3EREREVH347fFRERE5JEiIiLwq1/9Cn/6059w9uxZWK1WFBYWoqqqCj//+c8xaNAguUskL1VcXCx3CUTkhW6//Xbs2LEDVqsVBw4cwIULFzB48GC5yyIiIupzzp49i3379qGsrAwnT550uMzYsWMxc+ZMxMXFISgoyM0Veof+/XyRnBiKgo+OyF0KERH1IXfPHovBA/n1NBEREckrLCwMgYGBuHr1Ks6ePQuz2QylUil3WR6vqKhINB0RESFPIX0E9zcRERERUffzkbsAIiIiovaMGjUKv/rVrxAeHi7MO3jwINasWYOqqioZKyMior5m2LBhuPHGGwEATU1N+Prrr2WuiHoDs/kscnJew0jlYOTkvAaz+azcJREReaS6ujp8/vnnWLt2LX7729/io48+sgtODRw4ELNnz8ZvfvMbrFy5EnPmzGFwqhOpCycgciL3ERERuUdI8AAsuze88wWJiIiIepifnx8mTZokTLP7FBERERERUd/AW3sREVGfl5SUJJpmVxrPMmjQIDz99NPYunUrPvnkE1itVtTX1+OPf/wj5s6di/nz58PX11fuMomIqA+44447cODAAQDAl19+icTERPj48J4k5LpNm/6O377wPAAIf2dkPClnSUREHuPixYvQ6/UoKyvD4cOHYbVa7Zbx9/fH1KlTERsbi5iYGPj58eNuZ/j5+WDV4zFIf+EbXG5okrscIiLqxXx8FNA+Fo1+gfwcl4iIiDxDVFQUysvLAbSEpxISEmSuiIiIiIiIiHoav00mIiIij+fr64uFCxdi0qRJePfdd1FfXw+r1Yrt27dj//79WLx4MaKiouQuk4iIernIyEgEBwejtrYWZrMZer0esbGxcpdFXqw1MNV2muEpIurLLl68iPLycuzbtw9VVVVobm62W8bX1xdRUVG46aabMG3aNPTr10+GSnuPsaP64+XM6fjta9+h/sI1ucshIqJeKDDAByvTYzA5jN0OiYiIyHO0/W65uroaTU1NvGEnERERERFRL8fwFBEREXmNSZMmYeXKlcjPz0dFRQUAoLa2Fq+//jpiYmJw7733YvTo0TJXSUREvZVCocDs2bPx97//HQCwbds2qNVqdp8ilz274jmsX7dWmH7xpZdlrIaISB7nzp3Dt99+iwMHDrTbYUqhUCAyMhKxsbGYPn06Bg4cKEOlvVdM5FC88bs4/M8fynHYeEHucoiIqBcZFhSA1c/ciEkTGZwiIiIiz6JUKjFq1CicOXMGDQ0NOHLkCCIiIuQui4iIiIiIiHoQw1NERETkVQYNGoTHH38cu3btwkcffYTLly8DACoqKlBZWYnZs2dj7ty5GDRokMyVEhFRbzRz5kzs2LEDdXV1qK2txb59+xAXFyd3Wb2S2XwW+n1l+OyzYvz+lVflLqdHpKUtBwCsX7cWL770MpYsuV/mioiIep7VasWJEyfw7bff4ttvv4XJZGp32fDwcNx0001Qq9UICuJF1z1p1Ih++OOqWHxUYsKmbcfwo4VdqIiIyHV+vgrcownBg/dMwNCgALnLISIiInIoKioKZ86cAQBUVlYyPGUjKSnJ6eeLi4s73a7ZbEZZWRlqampQVFQkzNdoNIiMjER8fDxCQkKcrtfdY1gsFuzevdtuDLVajfj4eKfH6Kn9DbRcS1FdXY3q6mqUlJQI81UqFdRqNcLCwhAbGwulUim53vbqaluTTqfDtm3boNfroVKp8PTTT6OgoAB6vV5YZvPmzZ1+7mexWLB48WLRPFfWU6vVyMrKanfZqqoqlJaWwmg0impsPW+mTZsm+f8JZ/dLTExMh6+jO881IiIior5MYXV0K08iIg/Q+mHGzp072/3ltS/WQh1z5Vh19KEFebZLly5h69at0Ol0aG5uFub7+flhxowZmDVrFsLDw6FQKGSskoiIepsvv/wSf/vb3wAAo0ePxv/8z/90W/cp87mL3bIdb/frXz2DjRvzhOmzZnbBIKKeoRzBmy64Q3NzM2pqanDgwAF8++23OHfunMPlFAoFwsLCcOONN0KtVmP48OFurpQA4Oq1JmzdeRKf7DqJw8f53oSIiKQbMtgft6lH4YF7JiBY2U/ucoiIiIg6VFFRgZycHAAtIRKtVitzRZ6lszCPI51da5Gfn4+CgoJOt5OcnIwlS5a4FOZxxxiFhYXIzc2VNEZGRgaAzq9L6Yn9rdPpkJ+fD6PRKGl7ruwTR6/LbDZDq9U6HDczMxPZ2dnCdHZ2dofBIaDl32pmZqZonivrZWZmYu7cuaJlLBYLPvvsM0nHE2gJUqWlpXW6j5zdL+0dy54414iIiIj6MnaeIiKPpNVqRXfxkJMn1UId47HqewYOHIglS5YgISEBmzdvRmVlJQCgsbERpaWlKC0tRXBwMGbNmoWbb74ZAwYMkLliIiLqDWbOnIlPP/0UZ8+exenTp/H111/jtttuk7usXqVtcIqIiLzTxYsX8f3336OyshIVFRW4eNFxCMfPzw+TJ0/GjTfeiKlTp7LDlAcIDPBFSlIoUpJC8aPlGvQHz2N/5XmcPncVP1quoc5yDfUXroP3ZSMi6rsUCgWGDQnAiCEBGD40EBNDBmHmDCWmhAXBx4c3siIiIiLvEBkZCT8/PzQ2NuL48eO4ePEiBg3ijXZ6QkehEUeKioqg1+uRlZUlOcjjqWNYLBa3B/MsFgtycnJEXaakKCoqQlFRkaRgUkfWrVvX7j6y7dyk1+s7Hau6utrhPGfXsx27oqICGzZskHw8AaCkpAQGgwHZ2dlOf47Z0X6x5S3nGhEREZG3YXiKiDySJwVgPKkW6hiPVd8VHByMJ554AgcPHsQnn3wCg8EgPFdbW4t//vOf2LJlCyIiIhAVFYWoqCgEBwd3W5cQIiLqW3x9fbFgwQK8++67AFru+saLvYmIqK9ramrCkSNHUFlZiUOHDsFoNLYbrunfvz+mTp2KG2+8EVFRUQgMDHRztSTVsKAAzJkZjDkzg+UuhYioT9u2bRs+/vhjYfrRRx/FjBkzZKyIiIiIyPsFBAQgIiIC33//PaxWKw4dOoS4uDi5y/IYnXVGktrNpjXQ0TYEolarkZqaKgq/VFRUoKCgQLjuw2g0QqvVIi+v85utyTWGSqXC4sWLERMTg5CQEGG+wWBAcXExioqKUFJSgrFjx3a6/e7a30BLhyXb0E16ejri4+NFdZrNZhw5cgQffPCB6Hqb1u5QrgSodDod9Ho9VCoVli9fLvybMpvN2LRpEyIiIqBSqYT6dDodli5d2uE2t23b5nBeSkpKh+vt3btXeKxSqezCU227UqnVasyePdvuWFosFhw4cEDUwctoNKKgoEDo9CRFZ/ulrZ4+14iIiIj6MoaniIiIqNeIjo5GdHQ0Tp06hS+//BJ79uzBlStXALR0o/r+++/x/fffo7CwEAEBAQgNDUVoaChGjhyJ4cOHY/jw4Rg0aBACAgLg7+8Pf39/KBS8UyoREdmLjY3FZ599BpPJhCtXrmDTpk1IS0uTuywiIiK3Onv2LA4dOoTKykpUV1ejoaGh3WWHDRuGG2+8ETfeeCMiIiLg6+vrxkqJiIi827x583D06FFUVFQAAPLz8zFmzBgEBzPcSkRERNQVUVFR+P777wEA3333HcNTPSAnJ0cUAklPT3cYeomJiUFWVhaysrKEjklGoxGFhYWdhmTkGEOj0SAjI8PhjfUiIiIQERGBhIQEZGZmoqCgoMNtd6esrCy7OtPS0hx211IqlVAqlYiLi0NhYSFyc3OF5zZs2OBSd6X8/HyoVCq7jl5KpVIIGyUkJAj7xGg0wmw2t9v9y2w2O+y+1Nl6FotFFAhLSEhwuJyjkF1bQUFBSEhIQFRUFB544AFhflFRERYuXCgKMnVEyn5p5S3nGhEREZE3YniKiIiIep0xY8bgvvvuw3/9139Br9dj165dOHLkiGiZa9eu4fDhwzh8+LBMVRIR9Q6tFz77+vrCz88Pfn5+8PX1Rb9+/TBgwADhz8CBAzF06FCMGDECw4cPx4gRIzBw4ECvDan6+PjgoYcewtq1a9Hc3Ay9Xo/y8nJMmzZN7tKIiIh6zKVLl3D48GGhu9TZs2fbXdbHxwdhYWGIiopCdHQ0QkJCvPbnPhERkdwUCgUefvhhZGVlwWw24+rVq3jrrbfw61//Gv369ZO7PCIiIiKvFRMTg8LCQgBAeXk5rl27hoCAAJmr6j1KS0uFkBIAJCcndxpS0mq1MBgMQngkNzcXiYmJ7YZ43DFGRUWFaAyVSgWtVtvhGEDL+ZWdnS3qcNSTdDqdS3UCQEpKCmpra1FUVASgJZz02WefdbovbRmNRqxZs6bdUBPQElhqG/I5cuRIu8vbXuehVquFUFRH69kGrtRqtd0y7YXsHFEqlUhPTxcFzPbu3Ss5PCVlvwDec64REREReSuGp4iIiKjXCggIwC233IJbbrkFJ0+exBdffIGDBw+irq4Ozc3NcpdHRNQrNDU1CX9fu3bNqXUDAgIwYsQIuz+jR4/G6NGjPb4jRWhoKObOnYtt27YBAN5//32MHz8eQ4YMkbkyIiKi7lFXVweDwSD8OXnyZIfLjxgxAtHR0YiKikJkZCQv5iYiIupGAwYMwGOPPYZXXnkF169fR21tLd577z2kpaUxoExERETkouDgYIwZMwanTp3CtWvXUF5ejtjYWLnL6jU++OAD0XRqaqqk9RYvXozs7Gxhuqqqqt2uYO4Yw7abj9RAEtASaklOThZCST0pPz9fNO1MnUDLvmtbZ2ehMkfUanWnHdxUKpVo+tChQ+2uc+jQIdF68+fPF8JTHa1XXV3d4ZgAnA6GxcfHi8JTtbW1kteVsl8A7znXiIiIiLwVw1NERETUazU1NaG8vBy7du1CVVUVrFar3CUREfU6vr6+QoDKWdeuXcOpU6dw6tQph9sdM2YMxo0bJ/ozePBgj7oobO7cuThw4ABOnjyJ+vp65Obm4plnnuGdKZ00UjnY5efPmi9IWqftcibTcZSWfoMthZuxfftWLFuWhuXpv0R4eES741gsFlRXV2Hv3j04eqQGGzfmCc89u+I5TJo0GXFxNyMkJLTD1yK1xq6sd/BgBfT6MnxX/q1Q57JlaZg67Uao1bGIjo6RXKMjrds/ccKE9evWCvPb2w/Ovk5X90t3b+PwYQPKyw+gqup70et0dV+6ck7+859/F40NAIe+r4FSOdLp12M2n8WUyWHC9LMrnoNWu8rp7VDvZbVacfbsWVFYymw2d7hOQEAAJk2ahClTpiAqKgojR470qJ/TREREvU1ISAgeeOAB/OUvfwEA7N+/H59//jkSExNlroyIiIjIe6nVamzduhUAUFZWxvBUNzEYDELIBWjp8iM1hBMTI/7ctb2QjBxjqNVqRES0/12CI0lJST0eaGnbSQsANBqN03UGBQUhNTVVFODpKFTmyOzZsyWNo9FohA5LBQUFWLp0qcNldTqd8Hj+/PkYO3as6Ln21tu7d6/wWKPROBUAa49tl6mioiJkZGRIWlfKfvGWc42IiIjImzE8RdTLWCwW7N69GzU1NaJfhtRqNaKioqBWq0UfACQlJYnWLy4udmo8s9mMsrIyu/E0Gg0iIyMRHx8vqUWxbR1Sn2+vXovFgqqqKpSWlkKv1wsfEKhUKqjVaiQkJNh9ENLdtXS0b3U6HbZt2wa9Xg+VSoWnn3663XqA7tvPUusDWlqbO9p/CQkJdueRVN19fnb3edNRzQcOHLBr9R4XF+fUh0TkPnV1dfjqq6/w5Zdfor6+3uEy/v7+CA0NhUqlwsiRIzFixAgMGzYMgwcPhr+/PwICAuDn58cL/4iIOmG1WtHU1ISmpiY0NjYKf65cuYLLly/j8uXLuHTpEi5duoQff/wR586dE/501KmqqakJJpMJJpNJNH/QoEFCkEqlUkGlUmH06NGy/X/t5+eHn//853jllVfQ2NiIY8eOIT8/H7/4xS/4M8RDHTxYgdl3zBTN27gxDxs35jkM2FgsFnz+eTEee3RZu9tsG2558aWXkZHxZPcV7ASLxYKCgr/gty88b/dc27CXqzWWlZXij39Yj+3btzp83lP2Q1eZTMfxxz9ki/ZZW23nz5u3AE/997OIjXX994KOzsmdX3xtF57S7ytD0l3znB5n164vRNP33JPs9Daod7l+/TpOnjyJI0eOCGEpi8XS4To+Pj5QqVS44YYbEB0djbCwMPj58SNmIiIid7r55ptx9OhRfPFFy/u7LVu2QKVSITIyUubKiIiIiLzTjBkzhPDUwYMHcfnyZQwYMEDmqryfwWAQTU+bNk3yurbXv7TXDV2OMebPny95jFbOBmBcYVvnnDlzXNqOWq0Whac66u7kiNRriaZPny66BsdkMtkdE7PZLAqERUZGival0Wh0uJ7FYhGFkKZPny65/p4iZb94y7lGRERE5M34zTZRL5Kfn2/XvreVXq+HXq9HQUEB1Go1nnjiCafDNs6MV1JSgpKSEuTm5iI5ORlLliyBUqns0nhSFRYWitokt2U0GmE0GlFUVASVSgWtVuvWXxzNZjO0Wq3ol3uj0YjMzMx2Az3u3s86nQ75+fmiGtvWWlBQgIKCAmg0GmRkZEi+O4u7z8/usGPHDlGb9raKiopkO4+ofceOHcMnn3yC8vJyNDc3i57z8fFBWFgYoqOjERUVhXHjxsHHx0emSomIeg+FQgE/Pz/4+fkhMDBQ8npWqxUXL14UglRmsxnnz5/H2bNncfLkyXYv3r548SKqqqpQVVUlzOvXrx9CQ0Mxfvx4qFQqjB8/Hkql0m3hpdDQUCxduhTvvPMOgJb3NiNHjsTChQsZoPIwjkIqnS2/Nmt1u2EhR377wvM4eqQGv3/lVVdKdJnZfBaZzzwpqdbfvvA8LJZ6p7oO5eS85jCU1Z1jeILiT7bjwQeXSF5++/at2L59K956eyMWLVrs9HidnZPR0TGYN2+B6Lh+9lmxS+GpLYWbhcfz5i3ocgcy8i7Xr1/HiRMnhM9FjEYjTp48afd7ky1/f39MnDgRERERiIiIwMSJE536eU9EREQ9495774XRaMSRI0dgtVqRl5eH559/HkOHDpW7NCIiIiKvM2bMGAQHB6O2thZNTU04cOAAbr31VrnL8no1NTWi6a5cU1FSUgKtVusRY4SFhbk8Rk+yrXPMmDEubcf2d4r2QmXtkXoNkW2Ht5qaGrvrhCorK0XTKpUKAERdqxytZ3u9k7Pd5EwmE+rq6nD+/HmYzWbU1taKbjztCin7xVvONSIiIiJvxvAUUS/gKJDTEb1ej0ceeQQ5OTluGa+oqAh6vR5ZWVk9GqByti6j0YiMjAynu211xbp16yTXJ8d+7ih4ZqukpAR1dXXIysrqcDl3n5/dJSsrS3SXm/a0nkd/+9vf3BYQJHsWiwUfffQRvv76a1itVtFzw4cPx6xZszBz5sxuacVORETdQ6FQYPDgwRg8eDAmTJhg97zFYsHJkydhMplw4sQJnDhxArW1tWhsbLRbtqGhAT/88AN++OEHYV7//v2FIJVKpUJoaGiPBqpiY2Nx7tw5fPjhhwCATz75BBcuXMD999/PjhweZG3WaqeWdyZo1dbGjXmYMDHMrZ2Xfr/2ZadCXuvXrYV6xk2SQjhZWavtuh9JHSMoaIjT68lly5bNHXYY68hjjy7DwAEDnQ41STknF6UsFh3bjRvzsDz9lwgPl34hwMGDFaJtLEpxPuhF3uPatWswmUxCSOr48eM4depUp0EpoOXnZ2tQKjw8HCqVij/HiIiIPJCfnx8effRR/N///R8uXLiAixcv4q233kJmZiZ/dhMRERE5SaFQYMaMGdi+fTsAoLS0lOGpblBUVCSaTkpK8sox2nYwAuw7VnkK233hap2267UXKmuP1GsylEolVCqVcC1RRUUFEhISRMtUVFQIjzUajbDttl2rHK1XXV0tPFapVJ1ey2MwGFBeXo5t27Z1KSDVESn7xVvONSIiIiJvxk/Pibyco2CKSqXC4sWLERMTI/pFymAwoLi4WPiFubPQiyMWi8VuPLVajdTUVFGL4YqKChQUFAi/2BmNRmi1WuTl5Tncrm2AyfYDDSkBJ9u6kpOTkZSUJLqzjMViwZkzZ1BeXt5uSKg7anFEp9NBr9dDpVJh+fLlQltrs9mMTZs2iZbtqf3ckR07dgj7xNG+sz1/gJZf3AsLC5GSkuJwmz19fvbUsdqxY4fwQUt6ejoSEhKED1PMZjO2bdtm10UrLy/PqQ+MqHs0Njbiiy++wNatW9HQ0CB6LioqCnfccQeio6PZYYqIyAsFBQUhKCgIkydPFuY1NTXh9OnTOHHiBI4fPy5cFG77MwAArly5Ytehqn///ggNDYVKpRL+jBw5stsCVUlJSTh37hy+/PJLAMDu3btx7tw5PPbYY+jfv3+3jNFbnTVfEE2PVA7u8HlX7Nr1hRAeyX71NcybtwBK5UgAwOHDBvzzn3/vcP1ly9KQmJiEqOgYhISECvMtFgu+/XY/3n7rDVE45bcvPI8lS+4XxuhJxZ9sx8aNLb8DvPjSy7jrrnmiYM3hwwZ88sl2u85RDz64pNN9W/zJdofBqbfe3ohp06aLxrFYLDh+3Igvvvi3MJYz3arkVFZWahecmjdvAVJTf253zM3mszh0qNLumD/44BLsP1ApWrYjUs/JOXPsv/AvLz/gVHjqX/8qEk072iZ5n2vXruHMmTOora1FbW0tTp8+jZMnT6K2ttbuphLtGTVqFFQqFcLDwxEREYGxY8eyayIREZGXGDp0KH7xi1/gj3/8I5qbm3H06FFs3rwZ999/v9ylEREREXmduLg4ITxVXV0Ni8XCG3MSAPsuRtR95s+fL1ynVFRUhIyMDNHzba9Pmj59uvC47XVTjtbbu3evaIz2mM1m5OXlSbqxsjvwXCMiIiLqeQxPEXm5vLw80S9PGo0GGRkZDj/Eab1zcFxcHFauXOnSL105OTmi9dLT0x0GZ2JiYpCVlSXq3mM0GjsM2nTFjh07JNXVehFuREQEEhMT7e680pPy8/OhUqnsOkMplUq7X+Tl2M/Z2dnC320/aGjVev4EBweLgme5ublITEx0eM65+/zsLh3tC6VSiaVLl2LChAlYvfo/d4kvKSlBamoq7/ziRt9//z3+8Y9/4PTp06L5N910ExYuXIiRI3v+QmUiInIvX19fjB07FmPHjhWC6FarFWfOnMGxY8dgNBpx7NgxHD9+HNeuXbNb/8qVK6iurhbdca5fv34ICQmBSqUSth0cHIx+/fo5XZ9CocD999+P5uZm7N69GwBQVVWFtWvX4oEHHkBkZKSLr5y6w9tvvQEA2PnF14iOFr/HCw+PgFa7yuF6y5al4ecP/8JunVZBQUGYNesOTJkSBQCiMI1+X5nTnYhc8eCDSwA4fm1Ay+vLyHgSY8aMsQsIlZWVIjY2zuF2TabjwrZbPbviOaSlLXcYCgsKCkJ0dAyio2MQH38L5s3VuPqS3MpisdjV+uJLL7fbOUypHIlZs+7ArFl32HXl+uijIskdx6Sek0FBQXjxpZdFQbQthZuxaJG07lEWi0VU44svvcwLP7yI1WrFxYsXcfr0aZw6dQqnT58WwlLnz593alutQanWP6GhoQz3EhERebnIyEgkJyejsLAQQMtN3CZMmIBbbrlF5sqIiIiIvEtwcDAmTJiAo0ePwmq1Yt++fbjzzjvlLouoV7P93sxgMAg3eTaZTKLn2l67Y3tdjslkEuZZLBZRB6f2vpszGAx212q1UqvVUKlUCAsLw4ABAxAWFiaM2xPdzYiIiIjIfRieIvJiOp1OdPcLlUolqfNNXFwc1qxZg5UrVzo1XmlpqWi85OTkTgM6Wq0WBoNBCMJ0FLTpip07d4qmExMTO10nKCgIS5cu7dY6OmI0GrFmzZpO20HLuZ9XrVrlMDjVVkpKil2r6qqqKuEC5lbuPj+725o1azrcFwkJCVCr1aIPXSoqKhiecoOmpiZ89NFH+PTTT0Xzx40bh5/+9KeijmlERNT7KRQKjB49GqNHj0Z8fDwAoLm5GbW1taIw1fHjx3H9+nW79RsaGmAwGGAwGETzhw4dijFjxgh/goODMWbMGAwYMKDDenx8fPDggw8iJCQEmzdvRnNzM86cOYMNGzZg+vTpSElJ6fT9IPWM7du34q9/3dRuCMqRt97eKDmgolSOxKOPPS4KTxkOG+Cur9EKt3zc6WtbtGgxthRuFtV46NDBdsNTH31UJJqeN29BuyEzW7Gxcdj5xdeYfcdMScvL6cMPC0XT2a++hoceeljSulrtKpw/d07o/OVMxzFnzsk77hBfqLF9+1YcPFghad09X3/V4bZIXlarFRcuXMCPP/6Iuro6/Pjjj8Kf8+fPo7a2FpcvX3ZqmwqFwmFQypVgMBEREXm+OXPm4OjRo8Jn1e+//z7GjRuH0FBpHVGJiIiIqMXMmTNx9OhRAEBZWRnDU92suLi4V4xB3cf2mpy24amamhphvkqlsrsWJzk5WbhhdttrdWxv1NzedT9ZWVmiabVajdTU1E6vmSIiIiIi78bwFJEX27Ztm2haSjClVVxcnOgXSSk++OAD0XRqaqqk9RYvXix08gEcB226qm2ABYBH3kVbrVZLet1y7We1Wo2EhASXxiotLbUby93nZ3eSeqzuvfde0bnX9sMb6hnnz5/Hn//8Zxw5ckSYN2DAACxcuBC33347fHx8ZKyOiIg8hY+Pj9BFqvVu283NzTh9+jSMRiOOHz8u/H316lWH26irq0NdXR0OHTokmh8UFITg4GAMHz4cw4YNw9ChQzF06FDh8cCBA6FQKDB79mwEBwcjLy9PuOj9wIEDqKiowM033wy1Wo0bbrgBfn78tdxd5s1b4HQXKKnBqVat3ada7fn6K8ldiLpi2bI0zJp1h6RlU1N/LgpPnThhcricxWIRdToCgJf/7xWn6oqOjrHrmORpLBYLMp/5zzGaN2+B5OBUqyU/fUAITwHAoUOVko6HM+dkdHQM5s1bIO5spi+TFJ4qKPiLaExnAoTkuubmZly5cgWXL1/GpUuXhICU7Z+6ujo0Nja6NIaPjw+USiWCg4MxevRo4e+xY8cyKEVERNSHKBQKpKam4uTJk6itrcX169fx9ttv4/nnn+d7AiIiIiIn3HTTTfjnP/+JxsZGHDlyBOfOncOIESPkLstr2d6M1mKxdPu1PO4YQ6VSiQI5ZrPZI2+Sp9FoRDc4btuNyRm2HZ+Sk5O7WlqH2tZ94MABzJ07FwCwe/duYRlH1zLFxMQI1xS1Xa+6ulq0bUd0Op3omGo0Gqeuaeop3nKuEREREXkzXqVF5KUMBoPoAwC1Wu10t5WEhATJ4RTb8dLT0yV/4GB7V45Dhw51e3jKlqsfAvSk2bNnd7qMnPv53nvvlbys7Vi2d25x9/nZ3aTuizFjxoimbUN81L3Ky8uRn58vuuv6jBkz8MADD2DgwIEyVkZERN7Ax8dH6CJ18803A2jp9nH27FkhSFVbW4tTp07h3LlzsFqtDrdjsVhgsVjaHcfPz08IUg0bNgyxsbE4evSo8H6psbERX331Fb766iv069cPU6ZMwQ033IDRo0dDqVRC4dO/+188AQAWpTgXhHKFbbehtkGXnrTkpw9IXjbKJjizft1ah92kqqurRNPPrngOISHO37n+rrvmeXR4yvZ1PvXfzzq9jcjISaLp774rlxSecvactA2+ZT7zZKdBr4MHK0TrpKb+3Kkx+4KrV6+isbERTU1NaGpq6vRxY2MjLl++LISibB+3/n3lypVuq7Ffv36icFTr3yNHjmQIl4iIiAC0vF947LHHsHbtWly9ehVmsxl/+9vfsGzZMigUCrnLIyIiIvIKAwYMwI033oh9+/YBAL7++mvcfffdMlflvVQqlegaijNnzvRIsKmnx1Cr1aJrYmpra50OtBgMhm6tyZGxY8eKpk+dOuXSdVN1dXWi6eDg4K6U1ak5c+YI4amSkhIhxNQ2CKZWq+3WCwsLEx63XW/v3r2ibTvSNpgFtNxA2hN4y7lGRERE5M347TqRl7L9ZWf+/PlOb8OZVsO2402bNk3yura/jJ88eVLyulLZ3kGloKAAGRkZHtWBSsr+lnM/T5w40eWxbEND7j4/u5vUfWG7H2xDZNQ9mpubUVRUhM8++0yY5+fnh3vvvRcJCQn88p+IiFymUCgwatQojBo1CrGxscL8a9eu4fTp00KYqvXvs2fPorm5ucNtNjY24uzZszh79myn4zc0NGD//v3Yv3+/MO+l//296y+IOjRt2vQe2a7JdBz19fU4f/4cjh490vkKPWDChAmSl5UagDp06KBoOjHxLmdKEoSHO3cTBXezfZ22QSgpbH/vPHpEWkdaZ8/JW2beZjevrKwUsbHt3zTjiy/+3ek2+rpnnnlG7hIwcOBADBs2TPjTGsAdNmwYRo8ejaCgIP7eQ0RERJ0KDg7Ggw8+iHfeeQcAUFZWhsmTJ+PWW2+VuTIiIiIi73HrrbcK4aldu3Zh7ty5vHmNi9p2BgJariNx9qa7njBG25AO0NLZyNnrWcrLy7uzJIfUajUKCgqE6dLSUpdubG17/Y8z1y25wvb6nIqKCrsOuiqVym69kJAQUacmg8GAUaNGiepv79qftteXAZB8zvR0MMlbzjUiIiIib8bf7oi8VE2N+GIs21+genq8rnzY0PaOH93l7rvvFv1yW1JSAoPBgKVLlzps3ywHKUEuOfdzd7Z6dvf52d3Y9tpzXL9+HRs3bsSBAweEeSNHjkRaWhpCQ53vfEBERCRFQEAAQkND7X7WtAajTp8+jbq6OtTX1+PHH39EXV0d6urq8OOPP+L69esyVU2dGTlyVJfWN5vP4tChShw9egQXLlzwqG5Kth2vusOJEybRdE/fXVIu35V/K5oODxvX5W1u3JiH37/yaqfLOXtOBgUF4cWXXhade5999km74SmLxSJa9sWXXvaoG4z0dgqFAv3798fAgQMxYMAAu4BU2z8BAQFyl0tERES9RGxsLL7//nvhTur/+Mc/MHHiRIwZM0bmyoiIiIi8w+TJkzF69GicPn0aFy5cwL59+3DzzTfLXZZXioqKEk1v3rwZc+fO9box2t58DwByc3ORmJgo+bNWi8WC3Nzcbq3JEduQTVFRERYuXOhU9ymLxSIKYKlUqm4Po9lSKpVQq9VC6Km6uhoDBgwQntdoNO3u64SEBKFeg8GAhoYG4Tm1Wt3t1/4UFxd36/Zsecu5RkREROTNGJ4i8lK2HW56+gKotndqAYCkpKQeHc9ZMTExdt2njEYjVq9eDQBIT09HQkKCrKEYKcfI0/ezVO4+P6l3unjxInJzc0VhPLVajdTUVLs7DREREbmDn58fxowZ0+5FZ1arFVeuXBHCVK2BqosXL+L48eM4fvw4w1UycvU96cGDFfjLu3/Gxo153VyRZ1u/bq1oWmrHKm8j53F15Zy84447RdPr161FRsZTDre15+uvOlyXWgQEBMDPzw9+fn7w9fWV9Hf//v0xYMAAIRTV+rjtdP/+/dktioiIiGSxZMkS1NTUoLa2FtevX0deXh60Wi38/f3lLo2IiIjI4ykUCmg0Grz//vsAgH//+9+Ij4/n5zwuUCqVSE5OFq6DMRqNKCwsREpKiuRt5OTkICMjQ/Yx2oZ7AKCgoKDDddpqG0bqaZmZmcjOzhamX3/9dWRlZUle37bW5cuXd1ttHYmPjxeFp9p+3j19+vR215syZYrwuKamBpcvXxZtsz1tO1YBgMlk6jRkVlFRYXdNV3fzpnONiIiIyFsxPEXkpWzbJDOcAmi1WkRGRjq8i0Zubi5yc3OF4IWzbY3JOTw/qavMZjNef/11nDlzRpg3d+5c3HPPPfxgmoiIPJZCoRAunh87diwAYP/+/di0aRPq6+sdrhMUFITw8HCMHz/eqbv/kXu89967yHzmyU6XW7YsDRMmhiEiPAIPPrjEDZVRXxUdHYN58xZg+/atwrw9X3+FpLvm2S1bUPAX4fG8eQsQHc3fgx3ZsGGD3CUQERERdauAgACkpaUhKysLjY2NOHXqFP75z3/igQcekLs0IiIiIq9w880348MPP8Tly5dhNBpRU1OD8PBwucvySgsXLhQFTlqv5+ks3GQymfD6669Dr9d3GhxxxxhpaWmiZYqKihAcHNzpGPn5+T0euGlr7ty52Llzp3DNjl6vR1ZWFtLS0jq92XRhYaGoVo1Gg7i4uJ4sVzBt2jThcdubZgPosPPVxIkThcdFRUVITk52uE1bbTtWAS2hI61W2+7yFRUVyMzMbPf57uQt5xoRERGRt2J4ioh6lZSUFMTHx+Ojjz5y+EuhXq+HXq+HWq1GWlpaj7eXJiLnHT9+HK+//jouXLgAoOVC9Pvvvx+zZs2SuTIiIiLprl27hn/+85/46quv7J7z8/PDLbfcgrvuugsjRowQPWc+d9FdJVIntmzZbBecWrYsDTNvvQ2hoeMRHByMoKAhvFEAud2jjz0uCk999lmxXXjq4MEK0TKPPva42+ojIiIiIvmNHTsW9913n9Ax4csvv8SkSZNw0003yVwZERERkecLCAjArFmz8MknnwAAPvvsM4anXBQSEmLXDSk3Nxd79+5FamoqVCqV8Bm7xWKB0WiETqdzKgTijjEiIiKQnp4uuplze2OYzWYcOXIEH3zwgRBisl23J61YsQJarVborFRSUoKSkhKkp6cjPj5edCM/R7UCLZ2ZOgoTdbeOrt3q6DmlUinqItX2mHa0nkajEYWnWgNbixcvFq1nMBiwe/duYdnU1NQe7+7kTecaERERkTdieIqIXFJcXCx3Ce0KCQlBRkYGlixZAp1Oh23btonaLQMQ7hyzatUqJCQkyFRp5zx5PxP1BJPJhD/84Q9CO3V/f3/84he/6PCuQERERJ7mxIkT+POf/4za2lq752bOnIlFixZh0KBBMlRGUplMx/HYo8tE87bvKEFsrHvuskjyOWu+IHcJnbrxxhmi6Y0b8/Dr556HUjlSmPfFF//ucB0iIiIi6v1uv/12fP/999i/fz8A4K9//SvGjx/f6R3niYiIiAi444478Omnn6K5uRnffvstjh8/jtDQULnL8kpz587F5cuXRYGO1hsfd8SZAI87xkhJSUFtba0ooCNlDI1Gg5SUFLcFWpRKJbKyskQBKqAlgCOlBo1G49bgVCtHwaTU1NRO15s/f77d6+psvZCQELuQUWvIrD0ajQZLly7t8fAU4D3nGhEREZE38pG7ACJyjUqlEk2bzeYeHU+tVoumLRZLj47XHZRKJVJSUpCXl4fs7GxoNBq7ZVavXg2TySRDdY554352xN3nJ/UOJ06cEAWnBg4ciP/+7/9mcIqIiLxKTU0N1q9fbxecGjhwINLT0/HQQw8xOOUFSku/EU0Xbvm4zwWnnl3xnGjaZDru0nbM5rPdUU6PjfniSy+7vK5cgoKCkP3qa6J5u3Z9ITy2WCz47QvPC9PZr77GDmlEREREfZBCoUBqaiqGDx8OAGhoaMA777yDxsZGmSsjIiIi8nxDhw7FzJkzhel//etfMlbj/VJSUrBmzRq7a0nak5ycjOzs7A67B8kxRutNmqVatWqVLEEkpVKJvLw8pKenS15HpVLJVi8ATJkyRdI8W5GRkS6tl5KSgszMTEm1paamun2/eMu5RkRERORt2HmKyEup1WrRHUJqa2udvlugwWCQvKxKpRLdweLMmTNedfFVTEwMYmJicPfdd2PDhg2ifVdSUoKlS5fKWN1/ePt+buXu85O838mTJ/GHP/wBly5dAgAMGDAATz31FO/eRUREXqWmpgavv/46GhoaRPOHDh2Kp556CsHBwTJVRs76evdXoulZs+6QtJ6rASNPNG5ciGi68mAFQkKcf2926FBll2s5fNiA8HDpX2AfPXpU8rJjxoyxW7dtBydPdeutt4umtxRuxqJFiwEA3367v8NliYiIiKjv6N+/P37xi19g/fr1aG5uxtGjR/HRRx8hJSVF7tKIiIiIPN78+fPxzTffoLGxERUVFTh69CgmTJggd1leKy4uDnFxcSgtLcWhQ4dQWVkpuj4mOTkZYWFhiI2NdblbqjvGSEhIwObNm1FVVYXS0lJRdyCVSgW1Wo24uDhMmjRJ9ut9UlJSkJiYKNRqNBpF+0Oj0WDs2LFQq9WIiYmRsVJg0qRJkubZchSWk7Ie0NKx7NZbb8Xu3btx4MABUecpjUaDyMhIJCQkyNa915vONSIiIiJvwfAUkZcKCwsTTVdXVzv9i2x5ebnkZWNiYkS/hBkMBqfuvuIpYmJi8PTTT4vuHlJQUOAx4anesp/dfX6Sdzt16hQ2bNiAixcvAmj5Qp/BKSIi8jY1NTV47bXXcPXqVdH8oUOHYsWKFcKdvsk7bNyY59J6th2rvNmUKdGi6YKCvyDprnlOb+ftt95wep0XX3pZ1DmpvPyAU+GpTf/4m+RlIyMn263rDV3GwsMjsGxZmnCubt++VQiZ/eujImG5ZcvSnNp3RERERNT7TJw4EQsXLhS+e/jss88wadIkREdHd7wiERERUR83bNgwJCQkCIGKf/3rX3jyySdlrko+xcXF3bKd1oBTT+rpMYKCgoQxMjIyJK3j7P7rrv3dttae0J11urItV9dru/7cuXMxd+5cSZ2bpI7VE8evp841IiIior7ER+4CiMg1toGa3NxcWCwWyetbLBZs27ZN8vJRUVGi6c2bN0te19PIfbeUjvSW/ezu85O8V21tLf7whz8Iwal+/frhySefdHh3ICIiIk91/vx5vPHGG3bBKT8/PyxfvpzBqW5gNp+VdXwp72VNpuN47NFlbqjGPSIjxXdm3L59K957712ntvHee+9i+/atTo9t2w1qS+Fmyb9P7Nr1hVPht+joGMybt0CY3rgxD1u2OP97mMViQVbWaqfX64p7FiaLpsvLD+DwYYPo9dsuQ0RERER9009+8hNMmTJFmP7LX/6C+vp6GSsiIiIi8g533XUXAgICAACHDh1CRUWFzBURERERERGRqxieIvJSERERUKvVonkFBQWS1y8oKIDRaJS8vFKpRHJysjBtNBpRWFgoeX0AyMnJkbysbXDCbDY7NZYzbPejnLW4ez/3FHefn63ceayo686cOYM//OEPwoWwgYGBeOKJJzBhwgR5CyMiInJCY2Mj3n77bVy6dMnuuZ/97GcYP368DFV5v7ZhFqAlEONOy5aliaY//LDj9+Qm03E8/5tf9WRJbhcUFITsV18Tzct85knJwaL33nsXmc+4dhfWadOmi6a3b9+KnJw/drpeWVkpUhbd7fR4jz72uGj6sUeXORWgKisrxRO/fAzr1611euyuuPHGGaLpLYWbUV5+oMNliIiIiKhvUigU+PnPf46goCAAwMWLF7Fx40Y0NzfLXBkRERGRZxs8eDA0Go0w/Y9//APXrl2TsSIiIiIiIiJyFcNTRF4sLU18QV9RUZGkoE1+fj6KioqcHm/hwoWi6dzcXEnjmUwmaLVap8a0Dd5UVlZ2uHxOTo7koIxOpxNNx8fHd2stXeXO/dyT3H1+Au4/VuS6s2fP4tVXXxXubhoQEIAnnngCYWFhMldGRETknH/+8584duwYgJaL0VolJCRg5syZcpXl9X6SNFc0/dijy1D8yXZRB6rDhw091uln5q23iaYzn3kSWVmrcfiwQTT/8GEDtmzZjBnTo7B9+1a8+NLLPVKPXP7rv1Ls5j326DL8+lfPoKys1K4jmMl0HMWfbMfSh+4XglO2QTgpwsMj7NZbv24tlj50v924FosFBw9WICfnNcyb23IRg7PHYdasO+wCc489ugxLH7ofxZ9sh8l03G6d1tf66189g3lzNS512Ooq24Db9u1bsaXwP6Gv7FdfEy6OJSIiIiIKCgrCww8/LPzuWl1djU8++UTmqoiIiIg831133YVhw4YBAM6dO4cdO3bIXBERERERERG5QmG1Wq1yF0FErissLERubq5onlqtRmpqKlQqlXChlNlsxpEjR/Dmm28KHX0yMzORnZ0tWre4uLjD8Xbs2GG3jqPxLBYLjEYjdDqdKAjT2fZblZaWYuXKlaJ5a9asQVxcnPB6Nm3ahIyMDABAUlISAECj0WDOnDkYM2YMQkJCROsbDAaUl5eL9pdKpUJ2dnaHF5Q5W0ur1ppaSX3tgHv2c1fqk7q+u89POY5VV/djX2Q2m5GdnY26ujoA/wlORUREyFsYERGRk8rKyvDOO+/YzVepVFixYgX8/Pyc3qb53MXuKM3rHTxYgdl3SAufnTVfcDh/pHKwpOUcMZmOY8b0KMnLAy0hodf/9BbCw8ZJHtfVGrvy2pxd35lj4cjOL762W19KvWVlpUIYyhmuHAcAMJvPIvOZJ7sUgpo3bwHy3/t7u8939bg5cviwAbfc7Li71J5v9iM8nO+xO6McMUjuEoiIiIjc6sMPPxRCUwqFAs888ww/myUiIiLqRNtrTXx9fbFy5UoEBwfLXBURERERERE5w/kruYjIo6SkpKC2tlYUnNHr9dDr9R2ul56ejrlz59qFUzozd+5cXL58WRSIkTKeSqWCVquVPE5cXBzUarVou7ahGAB2IZiSkhKUlJRIGkOlUiErK6vTO3G7WktXuGs/9zR3n59yHCtyzrlz57BhwwYhOOXv74+MjAx+OU9ERF7n0qVL2LRpkzDt5+eHxsZGAMB9993nUnCK/iM6OgbPrngO69etlWX8kJBQ/PWvm/Dgg0skr/OcdlWv7PITHR3jMAAlxc4vvkZ0dIxL48bGxuGttzfisUeXSV5n3rwFLndbUipHCl2cXAlQtY7tbuHhEVi2LA0bN+aJ5i9blsbgFBERERE5dPfdd+OHH35ATU0NrFYr3nnnHaxcuRIDBw6UuzQiIiIijzVt2jRMnz4dBw4cQFNTE/7617/imWeegY+Pj9ylERERERERkUT8DY6oF8jIyMCqVaskLatSqbBmzRqkpKS4PF5KSgrWrFkDlUolafnk5GRkZ2c7HY5YsWJFh2O0fS4nJwdqtVrytltrUiqV3V5Ld3HXfu5p7j4/5ThWJM2PP/6IDRs24Pz58wBaglOPP/44IiMjZa6MiIjIeUVFRbh4saVL1MCBA4Xg1PTp0xEeHi5nab2GVrsKz654rsNl5s1b0GPjJ901D4VbPu50uXnzFmDPN/tdDgl5g+joGOz5Zj+WLUuTtPyyZWndsk8WLVos6Ri0jpn96mtQKke6PJ5SORKv/+ktvPX2RqfWe+vtjch/7+9dGrsrlvz0AUnziIiIiIiAlk4JjzzyCPr37w8AqKurw3vvvQer1SpzZURERESebcmSJQgMDAQAHD58GP/6179kroiIiIiIiIicobDyk3CiXsNisaCqqgqlpaWiTj8qlQpqtRpxcXGIi4sTrZOUlCSaLi4udmrM0tJSHDp0CJWVlaJuP8nJyQgLC0NsbKzkgFJ7dDoddu/eLXSUUqlUmD9/PhITE+3uKF5RUYHq6mpUV1eLOlCp1WqoVCrExMRg+vTpLt8R3plaurpv2+qJ/dzV+pxd393np7uOVXce596srq4Or776Ks6ePQugpTtHeno6oqKiZK6MiIjIeTU1NVi3bh0AQKFQAACsVit8fHzwwgsvYNSoUS5v23zuYrfU2JscPFgBvb4MnxbvEDoCLVuWhpm33oY5c5LafW8/UjlYNH3WfMGl8S0WC/Z8/RX0+/eJOmG9+NLLiI+/BbGx4vewzozrao1dfW1dWf/gwQpUV3+Pr3d/Jep29OyK5zBp0mRERk62C011tV6LxYLq6irs3bsHe77+SjgP5s1bgJ8kzYVaHeu2MYGW82/qtBsxZUq03fHvSHedk7YOHqyw6wzWXdvuC5QjBsldAhEREZEsDhw4gLfeekuYXrJkCWbPni1fQUREREReYNeuXXj//feF6SeeeILfeRMREREREXkJhqeI+ri2wQ+NRgOtVitjNURiPD97B4vFguzsbJw5cwZAy51Nly9fjpiY3tudgYj+H3v3Hl5VfeeL/7NDwkUBUaMCg1ExYrkUNQJWqqiptagzFim1HUtVWmwp7dxoO82v45l2emyH3qhTWw9tGekg9jaK1NYbtWnF1huaWo0wMAE0ZBQxIGxAEEL27w8O+7CTAElIsnJ5vZ6nz6zv2mut73uvveQcSN77C91XfX19fO1rX4tXX301IiKGDh2a3b700kvjuuuuO6rrK0/RHbVXaYj97rjj9vjSP38xO/7hjxbGtddOSzBR16I8BQD0ZD/72c9i+fLlERFRUFAQZWVlMWTIkIRTAQB0XplMJhYuXBjPPvtsRET0798/vvjFL8agQYOSDQYAAMAR5SUdAEhOTU1Nzri1qzFBe/B8dg/bt2+P2267LVucysvLi5tvvllxCoAu69lnn82Wpfr16xdbtmyJiIjevXvHVVddlWQ0oAeqrX0jpzgVETF+/AUJpQEAoKv5wAc+kC1L7d27NxYuXBh1dXUJpwIA6LxSqVR85CMficGDB0dExI4dO+IHP/hB7N69O+FkAAAAHInyFPRgr732Ws5YmYHOxPPZ9e3YsSP+7d/+LTZu3BgR+4tTH//4x2Ps2LEJJwOA1qmvr48HH3wwOx45cmT2B6Ljx4+P/v2tXgJ0rMcffyxnPGPGzBg27NSE0gAA0NUUFBTEjBkzIj8/PyL2f6nZ/fffn3AqAIDOrU+fPnHzzTdH7969IyLilVdeiTvuuCP27NmTcDIAAAAOR3kKerDf/va3OeNRo0YllAQa83x2bTt37ozvfve72ZU5UqlUzJgxI84777yEkwFA6z377LPZ1RQHDRoU//M//5N9bdKkSUnFAnqwT9w8I2d83YeuTygJAABd1bBhw+Kaa67Jjn/729/G6tWrE0wEAND5DRkyJD760Y9GKpWKiIiqqqr40Y9+ZBVPAACATkx5CnqompqaKC8vz45LSkqisLAwwUTw/3g+u7Zdu3bF7bffHjU1NRGxvzh14403xvnnn59wMgBovYarTo0dOzZef/31iIg4/fTT49RTrfQCdKyGq05deeXVMW7c+ITSAADQlb3nPe+Js88+OyIiMplM/Md//Ee89dZbCacCAOjczj///Pjrv/7r7Pill16KhQsXxt69exNMBQAAwKEoT0EP9eUvfzlnPH369GSCQBM8n13X7t274/bbb4/q6uqI2F+c+uhHPxoTJkxIOBkAHJ0//elP2VWnBg4cGG+++Wb2tYsvvjipWEAPVVOzIaZe+5c5+27+xKcSSgMAQFd34AuwjjnmmIiI2Lp1a/z0pz+NTCaTcDIAgM7toosuimnTpmXHf/rTn+I73/lObNu2LcFUAAAANEV5Crq4mTNnxvLly5t9fE1NTZSVlWWLDRERpaWlMWbMmPaIRw/n+exZduzYEd/97nfj5Zdfzu67/vrr413veldyoQCgjTz22P9b4eWyyy6LVatWRUREv379rK4ItKva2jey2+l0Oh5//LE479xROcfMmDEzLr74ko6OBgBANzJo0KC4/vrrs+PnnnsunnnmmQQTAQB0DaWlpXHNNddkxy+//HLMnTs35+fmAAAAJC8/6QDA0amuro5bb701IvavzlNSUhKDBw+OwsLC7DG1tbWxcePGqKioiMWLF+ecX1RUFDNnzuzQzPQcns+eY/PmzfG9730vXn/99ey+v/7rv453v/vdCaYCgLbx6quvRlVVVURE9OnTJ4477rioq6uLiIgLLrggevfunWQ8oJsb+Y7hRzzmb/9uTgckAQCguyspKYkLLrggnn766YiI+PnPfx7FxcVx4oknJpwMAKBzmzx5cvTr1y/+8z//M+rr62Pbtm0xb968mDp1akyaNCny8ny/OQAAQNJSmUwmk3QIoPVmzpyZs0pPS5SWlsbMmTNziizQljyfPUNNTU18//vfj23btkVERCqVig996EMxadKkhJMBQNv46U9/Go8//nhEREyaNCl27NgRFRUVERHx93//9zFixIg2m6t28442uxZ0FicVDsgZv1G7PaEkXVPD+9fQ7x97MkaPtlpvaxWe2D/pCAAAncru3bvjq1/9amzevDkiIoYPHx5z5szxC78AAM1QVVUVP/rRj2L79v/3b6CnnnpqfPjDH44zzjgjwWQAAAD4V27o4ubNmxezZs1q0TlFRUVxyy23RFlZmWIK7crz2f2tWbMm5s2bly1O5efnx8yZMxWnAOg2du3alf3G7YiId73rXVFZWRkREf369YszzzwzqWhAD3fllVfHU0//SXEKAIA21bdv37jpppsilUpFRMS6devi4YcfTjgVAEDXUFxcHGVlZXHaaadl923YsCG++c1vxl133RXpdDrBdAAAAD2blaegm0in07F69epYtWpVrFy5MvtN+BH7yyglJSUxfPjwKC4ujuLi4gST0hN5PrufTCYTf/zjH+MXv/hF1NXVRcT+XyD/1Kc+5TMEoFt5/PHH46c//WlE7P+27SuuuCLmz58fERHjx4+PGTNmtOl8Vp6iO7Ly1NGZO/fW+Pa3vp4df/ZzX4h3v/viuPjiSxJM1X1YeQoAoGm/+tWv4qGHHoqIiLy8vPjc5z4Xp59+erKhAAC6iL1798ZvfvObeOSRR2Lv3r3Z/Xl5eXHOOefERRddFO94xzuyhXUAAADan/IUANAib7/9dvz0pz+NZ555Jrvv+OOPj8985jMxZMiQBJMBQNv79re/HWvXro2IiBtuuCFWr16dXYnq4x//eJx//vltOp/yFEDHUp4CAGjavn374tvf/na8/PLLERFx0kknxRe/+MXo06dPssEAALqQLVu2xH333RfPPfdco9dOPPHEuPDCC+Pss8+OoqKiKCgoSCAhAABAz6E8BQA022uvvRY/+tGPYuPGjdl9p556anzqU5+KQYMGJRcMANpBbW1t/PM//3NERPTu3Tv+9V//NW655ZbYtWtX5OXlxTe/+c3o169f286pPAXQoZSnAAAObdOmTfG1r30t9uzZExEREydOjOnTpyecCgCg6/nv//7vuP/++7Nf1tZQr169oqioKIYPHx6nnnpq9O/fP4455pg49thj45hjjol+/fpFXl5eB6cGAADoXvKTDgAAdH6ZTCaefvrp+NnPfpb9QXlExKRJk+IDH/iAb8ECoFtasWJFdnvs2LHxxhtvxK5duyIiYsSIEW1enAIAAIDO5OSTT44PfvCDcffdd0dExBNPPBFjxoyJc889N9lgAABdzFlnnRWf/exn47XXXos//vGP8fTTT8fOnTuzr+/bty/Wr18f69evb/L8Xr16xb59+zoqLkCbuPrqq+Pqq69OOgYAQJbyFABwWK+99lr8/Oc/jzVr1mT39e7dO6ZPnx7jxo1LMBkAtJ9MJhPPPPNMdjx+/Pic/7dw1KhRScQCAACADjVx4sR48cUX44UXXoiIiLvvvjvOOOOMOO644xJOBgDQ9QwZMiSmTZsW73//++PPf/5zrFy5MtatWxebNm067HmKUwAAAEdPeQoAaNLu3bvjwQcfjPLy8qivr8/uHzp0aMycOTMGDx6cYDoAaF81NTXx+uuvR0TEscceGyNHjozHH388+/pZZ52VVDQAAADoMKlUKqZPnx633nprpNPp2LlzZyxatCg+85nPRCqVSjoeAECXVFBQEOPGjct+WemOHTuyK0+9/vrr8eabb8bWrVvj7bffjrq6ushkMlFXV5dwagAAgK5NeQoAyLFv37549tlnY+nSpbFt27bs/ry8vCgtLY2//Mu/jN69eyeYEADa34svvpjdPu+88yIvLy+qqqoiYv8KjKeeempS0QAAAKBD9e/fP2644Yb43ve+FxERq1atit///vdx2WWXJZwMAKB76N+/f7zzne+Md77znUlHAQAA6LaUpwCAiIjYvn17/OEPf4jHH388tm7dmvPaO97xjrjuuuusNgVAj3Fweeqcc86JDRs2xO7duyMiYvjw4ZGXl5dUNAAAAOhwo0aNiksvvTR+//vfR0TEfffdF2effXYMHTo02WAAAAAAANAMylMA0MO9/PLL8fvf/z4qKiqirq4u57Xjjz8+pk2bFueee26kUqmEEgJAx0qn0/HKK69ERERBQUGMGDEi+8thERHFxcUJJQMAAIDkXHvttbF69ep47bXXoq6uLu688874whe+EAUFBUlHAwAAAACAw1KeAoAeZs+ePbFu3bqorKyMysrK2LRpU6NjBg0aFJMmTYrS0tLo3bt3AikBIDkvvfRSdvvss8+OgoKC+O///u/svjPPPDOJWAAAAJCogoKCmDFjRnzjG9+Iurq6ePXVV+OXv/xlTJs2LeloAAAAAABwWMpTANCNZDKZ2Lt3b+zZsyf27t0b6XQ6tmzZEps3b46NGzfGyy+/HK+99lpkMpkmzx8xYkRccsklMXbs2OjVq1cHpweAzqGysjK7PWbMmMhkMrF27dqIiMjLy4szzjgjqWgAAACQqGHDhsU111wTS5YsiYiI8vLyGD16dIwcOTLhZAAAAAAAcGjKU9AGHnjggXjggQeSjgEQvXr1in379rXonL59+8b48ePjkksuiaFDh7ZTMgDoGurq6mLVqlXZ8ZgxY6K2tjZ27doVERFFRUVWZQQAAKBHe8973hMvvfRSrF69OiIiFi1aFLfccksce+yxCScDAAAAAICmKU8BQDfSnOJUKpWKIUOGxMiRI2PMmDFx5plnRn6+/y8BAERErF27Nnbv3h0REUOGDIkTTjghKioqsq+fdtppSUUDAACATiGVSsWNN94Yt956a7z11luxbdu2uPvuu+Pmm2+OVCqVdDwAAAAAAGjEb0oDQDeSn58feXl50bt37+jdu3ccc8wxceKJJ8YJJ5wQhYWFUVRUFKeeeqoVMwDgEF588cXs9pgxYyIiYsOGDdl9w4YN6/BMAAAA0NkMGjQorr/++liwYEFERDz//PPx5JNPxsSJExNOBgAAAAAAjSlPQRu4+uqr4+qrr046BgAAcJQqKyuz28pTAAAAcGglJSVxwQUXxNNPPx0REb/4xS/irLPOipNOOinhZAAAAAAAkCsv6QAAAADQGWzatCk2bdoUERH9+vWL4cOHRyaTierq6oiIyMvLi6FDhyYZEQAAADqVD33oQ3HiiSdGRMSePXvixz/+cdTX1yecCgAAAAAAcilPAQAAQOSuOjVy5Mjo1atXbNu2LXbs2BEREaecckoUFBQkFQ8AAAA6nb59+8ZNN90UqVQqIiLWr18fDz30UMKpAAAAAAAgl/IUAAAARMTq1auz26NHj46IyK46FRFx6qmndngmAAAA6OzOPPPMmDx5cnb84IMPxrp16xJMBAAAAAAAuZSnAAAA6PEymUysXbs2Oz777LMjImLDhg3ZfcOGDWv3HAe+qRuA9peX589cAIC2ctVVV8Xpp58eEfv/jv3jH/84du/enWwoAAAAAAD4v5SnAAAA6PFee+21eOuttyIiYtCgQXH88cdHRMTGjRuzx/zFX/xFu+fwi/wAHUdhFQCg7fTq1Stuuumm6N27d0RE1NbWxi9+8YuEUwEAAAAAwH7KUwAAAPR4VVVV2e3i4uLsL9QfXJ4aOnRou+fwi/wAHUdhFQCgbZ188snxwQ9+MDt+6qmn4k9/+lOCiQAAAAAAYD/lKQAAAHq8huWpiIj6+vrYtGlTRET07t07Bg4c2O45CvL9NR2goxQU9Eo6AgBAtzNx4sQYO3Zsdnz33XfH1q1bkwsEAAAAAAChPAUAAEAPl8lkmixPvfnmm7F3796IiDjllFM6ZFUov8gP0HF6F+QnHQEAoNtJpVIxffr07BeQvPXWW/Ef//EfkclkEk4GAAAAAEBPpjwFAABAj7Zly5bst2Afc8wxMWTIkIiIeP3117PHnHzyyR2SpaCgV3RARwugx8vLS0W+1f4AANpF//7944YbbsiOV69eHb/97W8TTAQAAAAAQE/nNwQAAADo0Q5ederMM8/MrjC1cePG7P5TTjmlQ7KkUqno07ugQ+YC6MmOOaZ30hEAALq1UaNGxaWXXpod33///VFTU5NcIAAAAAAAejTlKQAAAHq0huWpA5JYeSoiom8/5SmA9tSrV1707ePPWgCA9nbttddmV3euq6uLO++8M/bs2ZNwKgAAAAAAeiLlKQAAAHq0g8tTxcXF2e2DV57qyPJUfq+86NfXL/UDtJcB/fskHQEAoEcoKCiIGTNmRH5+fkTs/3v2kiVLEk4FAAAAAEBPpDwFAABAj5VOp7MrTOXn50dRUVH2tYNXnjrppJM6NNcxx/SJ/F7+yg7Q1vr37xP5+b2SjgEA0GMMGzYspkyZkh0vX748XnzxxeQCAQAAAADQI/lNLAAAAHqstWvXZrdPP/307Ldh7927N9LpdEREHHvssXHsscd2aK5UKmLgwH4KVABtJJXaX5zq28fKfgAAHe2yyy6LkSNHZsd33XVX9u/cAAAAAADQEfwWFgAAAD1WVVVVdru4uDi7/eabb2a3TzjhhA7NdEBeXiqOO65f9O6dn8j8AN1Fr155cdzAfopTAAAJSaVSccMNN2S/mGTHjh2xaNGiyGQyCScDAAAAAKCnUJ4CAACgx2pOeer444/v0EwHS6VSMXBA3zhuYL/Iz/dXeICWyMtLRf/+feL4QcdEfn6vpOMAAPRoxx13XEyfPj07XrlyZfz+979PLhAAAAAAAD2K37wCAACgR9q9e3fU1NRExP6S0vDhw7OvdYaVpw5WUNArBh13TBw/6Jg49pjeUVDQK3r1you8vFTS0QA6hby8VPTqlRcFBb3imGN6x6DjjokTjj/WalMAAJ3IOeecExdddFF2fN9998Wrr76aYCIAAAAAAHqK/KQDAAAAQBLWrVsXmUwmIiKGDRsWffv2zb62ZcuW7HaSK0811KtXXvTr1zv69Us6CQAAALTctGnTYs2aNbFp06aoq6uLO++8M77whS9EQYHSOwAAAAAA7cfKUwAAAPRIVVVV2e0zzzwz57WDy1ODBg3qqEgAAADQrfXu3Ts+9rGPRV7e/h9Tv/rqq7F06dJkQwEAAAAA0O0pTwEAANAjHVyeKi4uznntzTffzG53ppWnAAAAoKsrKiqKa665Jjv+3e9+Fy+99FKCiQAAAAAA6O6UpwAAAOhx6urq4uWXX86OG648pTwFAAAA7efyyy+PESNGZMd33XVXbN++PcFEAAAAAAB0Z8pTAAAA9DivvPJK1NXVRUTESSedFMcdd1z2tUwmE1u2bImIiFQqlfMaAAAAcPTy8vLixhtvjH79+kVERDqdjrvuuisymUzCyQAAAAAA6I6UpwAAAOhxqqqqstsNV5166623Ys+ePRERMWDAgMjPz+/QbAAAANATHH/88fGRj3wkO66srIzHH388wUQAAAAAAHRXylMAAAD0OAeXp4qLi3Nee/PNN7Pbxx9/fIdlAgAAgJ6mpKQk3vWud2XH9957b7z22msJJgIAAAAAoDtSngIAAKBHqa+vj7Vr12bHDctTW7ZsyW4rTwEAAED7uu6666KwsDAiIvbu3Rt33nln1NXVJZwKAAAAAIDuRHkKAACAHuV//ud/Yvfu3RERMWDAgDjppJNyXleeAgAAgI7Tt2/fmDFjRuTl7f/R9f/8z//EL3/5y4RTAQAAAADQnShPAQAA0KNUVVVlt88888xIpVI5r7/55pvZbeUpAAAAaH9nnHFGXHXVVdnxb3/721i5cmWCiQAAAAAA6E6UpwAAAOhRDi5PnXXWWY1eV54CAACAjjd58uQ488wzs+Mf//jHsW3btgQTAQAAAADQXShPAQAA0GNkMpmc8lRxcXGjY7Zs2ZLdHjRoUEfEAgAAgB4vLy8vbrrppujXr19EROzYsSN+/OMfR319fcLJAAAAAADo6pSnAAAA6DHeeOON2L59e0RE9O3bN/7iL/6i0TFWngIAAIBknHjiiTF9+vTsePXq1fHII48kmAgAAAAAgO5AeQoAAIAe4+BVp84888zIy8v9a3F9fX1s3bo1IiJSqVQcd9xxHRkPAAAAerzzzjsvJk2alB3/+te/zvn7PAAAAAAAtJTyFAAAAD3Gwb9sVVxc3Oj1rVu3RiaTiYiIgQMHRq9evTosGwAAALDfBz7wgRg2bFhERGQymbjzzjtjx44dCacCAAAAAKCrUp4CAACgx/jv//7v7PZZZ53V6PV0Op3dPv744zskEwAAAJCroKAgZs6cGb17946I/V92smjRouwXngAAAAAAQEsoTwEAANAjbN26NTZv3hwR+38Jq6ioqNEx27dvz24PGDCgw7IBAAAAuU4++eS4/vrrs+PKysooLy9PMBEAAAAAAF2V8hQAAAA9QlVVVXb7jDPOiPz8/EbHKE8BAABA5zFhwoS48MILs+OlS5fGK6+8kmAiAAAAAAC6osa/KQYAABGRTqfjiSeeiOeffz77ja6lpaUxffr0GDZsWMLpOqcrrrgiZ7xs2bIWne+e01xH+6z1VAeXp4qLi5s8ZseOHdnt/v37t3smAAAA4PA+9KEPxfr162Pjxo2xb9++WLBgQXzxi1+Mfv36JR0NAAAAAIAuQnkKAIBGKisr47bbbovq6uqc/eXl5VFeXq6o0Q7cc2h/B5enzjrrrCaPUZ4CAACAzqV3794xc+bM+PrXvx579+6NzZs3x9133x0f//jHI5VKJR0PAAAAAIAuIC/pAAAAdC6VlZUxZ86cRiUe2o97Du1v586d8eqrr0ZERF5eXpxxxhlNHrd9+/bs9oABAzokGwAAAHB4Q4cOjeuuuy47rqioiD/84Q8JJgIAAAAAoCux8hQAAFnpdDpuu+22nH2zZs2Kyy+/PAYOHBjpdDoWL16cTLhuyj2HjrF27drs9mmnnRa9e/du8jgrTwEAAEDnNHHixFi9enU8++yzERFxzz33xJlnnhlDhw5NOBkAAAAAAJ2dlacAAMh64oknclY/mj59ekydOjUGDhwYEREDBw6M2bNnJxWvW3LPoWOsXLkyuz1ixIhDHqc8BQAAAJ1TKpWK66+/Pk466aSIiNi7d28sWLAg9uzZk3AyAAAAAAA6O+UpAACy1q1blzOeOHFiQkl6DvccOsaqVauy26NGjTrkcdu3b89uK08BAABA59K3b9/4+Mc/Hr169YqIiI0bN8bPfvazhFMBAAAAANDZKU8BAJC1dOnSnHFxcXEyQXoQ9xza3xtvvBFvvPFGROz/JaszzjjjkMcevPLUgAED2j0bAAAA0DJFRUUxderU7Pipp56KZ555JsFEAAAAAAB0dspTAAAAdGsHrzo1YsSIyM/Pb/K4PXv2xJ49eyIioqCgIHr37t0h+QAAAICWufTSS2Ps2LHZ8U9+8pPYtGlTgokAAAAAAOjMlKcAAADo1lauXJndHj169CGP2759e3bbqlMAAADQeaVSqfjoRz8axx9/fETs/0KUBQsWZL8UBQAAAAAADqY8BQAAQLdVV1cXq1evzo5HjRp1yGN37NiR3e7fv3+75gIAAACOzrHHHhsf//jHIy9v/4+8a2pq4qc//WlkMpmEkwEAAAAA0NkoTwEAANBtrV+/Pt5+++2IiDj55JPjxBNPPOSxB688pTwFAAAAnd/w4cPj/e9/f3b89NNPx/LlyxNMBAAAAABAZ5SfdAAAAJJzxRVXtPj1ZcuWHfG6tbW18eyzz8a6deti6dKl2f2lpaUxYsSImDBhQgwbNqzFeTt6jnQ6HU888USjOUpKSmLChAmtmqO97nlERGVlZaxZsybWrFkT5eXl2f1FRUVRUlISw4cPj3HjxkVhYeFRZT44z/Lly+PBBx+MioqKKCoqir//+7+PxYsXR0VFRfaYe+65JwYOHHjYOdLpdEybNi1nX2vOKykpiblz5x72+NWrV8eKFSuiuro6J+eBZ2fs2LFRXFx82HkjWn5fxowZc9hcbf2ssd/KlSuz26NHjz7ssQevPDVgwIB2ywQAAAC0ncsvvzzWr18fzz//fERE/Od//meceuqpMXz48GSDAQAAAADQaShPAQDQphYtWhSLFy9u8rXy8vIoLy+P+fPnx5QpU+K6665rcZGno+ZYsmRJzJ8/v8nXKioqoqKiIjvH7NmzW3z9trR8+fJYtGhRVFdXN/l6dXV1zmtHc18OqK2tjbKyspzrVldXx5w5c2LOnDk5paTq6urDFocOHNPUvpaed+mllzZ5XDqdjkcfffSQn2nE/3t2IvYXqWbOnNnie3S4+3KoElxXeta6ooPLU6NGjTrssQeXp6w8BQAAAF1DKpWKG264ITZu3BgbN26M+vr6+NGPfhRlZWVx3HHHJR0PAAAAAIBOIC/pAAAAdA+1tbUxc+bMQ5aaGlq6dGmUlZVFbW1tp5zjcCWbhnMcbqWj9pROp2Pu3Llx6623HrI41ZSlS5fG9ddfH5WVla2e+1vf+tYh52y4atPBRapDWbNmTbP2HemYplaMqqysjDlz5jT7M43YX6QqKyuLdDrd7HMiDn9fGupKz1pXtX379tiwYUNEROTn58dZZ511xOMPUJ4CAACArqNv377xiU98Ivr06RMREdu2bYsFCxbEvn37Ek4GAAAAAEBnYOUpAIAerOFKOFdcccVhXz+UdDrdaLWdkpKSmD59es7KQZWVlbF48eJsmaa6ujrKyspiwYIFnXaOoqKimDZtWowZMyaGDRuW3V9VVRXLli2LpUuXRnl5eQwdOvSI149ou3seETFnzpxGRZ1Zs2bFhAkTcrLW1tbG+vXr4957780pMs2ZMyfmzZt3xNWdGlq+fHlUVFREUVFRfPKTn4zx48dn5/nFL34RxcXFUVRUlM22fPnyuOGGGw57zQcffLDJfVOnTj3sec8880x2u6ioqMny1Jw5c7LbJSUlcemllzb6PNPpdDz//PM5K3hVV1fH4sWLm73a05Huy8E64lkjYtWqVdnts846K3r37n3Y4w9eeWrAgAHtlgsAAABoe4MHD44bbrghfvSjH0VExNq1a2PJkiXxwQ9+MOFkAAAAAAAkzcpTAAActTvuuCOnBDJr1qyYO3duo1LOmDFjYu7cuVFaWprdV11dHUuWLOmUc5SWlsa8efNi8uTJOWWWiP0rHM2ePTvmzZsXEdHs1bDayty5cxtl/clPfhJTp05tlLWwsDDGjx8fc+fOjVmzZuW8dtttt7V4daVFixZFUVFRzJ07N1sQOjDPgaLRpEmTsvurq6sPu/pXbW1tk6s1Hem8dDqdUwY7eM6GSkpKYt68eTF37twmP8+BAwfGpEmTGq3stHTp0qipqTnkdQ/WnPtyQFd61rqyg1dXGzly5BGPP7g8ZeUpAAAA6HrOO++8nC8r+t3vfpfz5TsAAAAAAPRMylMAAByVFStWRHl5eXY8ZcqUI64WVFZWFkVFRdnx/PnzD1vg6Yg5Kisrc+YoKiqKsrKyGDhw4GHnGTNmTLbU0lGWL1/eZNbCwsIjnjt16tSYMmVKdlxdXR2PPvpoi+avrq6OT37yk4edr6SkJGe8fv36Qx7b8LWDzz3ceQ0LVw3nPOBQRbumFBYWNiqYNfcXbJpzXyK61rPWle3ZsydeeOGF7Lg5n//27duz28pTAAAA0DVdc801cfbZZ2fHd999d7O/HAcAAAAAgO5JeQoAgKNy77335oynT5/erPOmTZuWM169enWiczRczaesrKxZc0TsL2UcXEhqb4sWLcoZtyRrROP7d6RiWUMlJSU5Kys15eDiWkTEqlWrDnnswa8VFRXFVVdd1azz1qxZc9g5DzhS0a6hCRMm5Iw3btzYrPOac18iutaz1pW98MILsWfPnoiIGDJkSAwePPiI5xxcnhowYEC7ZQMAAADaT15eXnz84x+PE044ISIi9u7dGz/4wQ9i586dCScDAAAAACApylMAALRaVVVVVFRUZMezZs064uo5BzRcBeZQJZkk5igpKYni4uJmzXHAFVdc0aLjW6uqqipnxaXS0tIWZx04cGCjAtXhimUNXXrppc2ao7S0NDtuWBg62PLly7PbV111VQwdOrTJ1xo6eEWo0tLSZj8XRzJs2LCc8dKlS5t1XnPuS1d61rq6FStWZLcPtSpZQzt27MhuW3kKAAAAuq7+/fvHzTffHPn5+RERsXnz5li4cGHU19cnnAwAAAAAgCQoTwEA0GpVVVU547Fjxzb73IYFlVdffbXTzHHwykfN1dICTGs1zPqe97ynVddpWCY53ApPDTUspR3KueeemzOuqalpdExtbW1OGWzEiBE597K6urrJ89LpdE4JqeFcSWjOfelKz1pXtnPnzli5cmV23Jzy1N69e+Ptt9+OiIhevXpF37592y0fAAAA0P5OO+20+PCHP5wdr1y5Mh588MEEEwEAAAAAkBTlKQAAWm3dunU546MpdZSXl3eaOYYPH97qOdpbw6xDhgxp1XUGDRqUMz5UsawpzV3hady4cTnjhtkjIqfgEhFRVFQUEZGzalVT5x1cuGpqruaoqamJysrKWL58eSxZsiTuuOOOmDlzZqtXdmrOfelKz1pX9vzzz8e+ffsiImLw4MHN+u+k4apTqVSq3fIBAAAAHWPixIlx0UUXZccPPvhgvPjiiwkmAgAAAAAgCflJBwAAoOtaunRpzri1pZOk5zh4BaOIxitWdSYN70drszY8r7y8PMrKypp1bnPLU4WFhVFUVJQtOlVWVsakSZNyjqmsrMxul5aWZq997rnnZstuTZ23Zs2a7HZRUVEUFhYeMU9VVVW88MIL8eCDDzYqX7WF5tyXrvSsdWXPPvtsdrs5q05FNC5PAQAAAN3DddddFzU1NfHyyy9HRMTChQujrKwsTj755GSDAQAAAADQYaw8BQBAj9ceRRr2u+qqq7LbDYtfDfede+652e0xY8Yc9rxnnnmmyTmaUltbG3Pnzo3Zs2fH/PnzE/28PWvtb9u2bTnluuauSrZ9+/bstvIUAAAAdB/5+fnxiU98Ivv3/d27d8cPf/jDePvttxNOBgAAAABAR7HyFAAA0G5GjBiRM66qqori4uKIiKipqcl57eDCVMMVmWpqarL70ul0zgpODedoON/s2bObfK2kpCSKiopi+PDhccwxx8Tw4cOzc7fHCmd0jIqKishkMhERcfrpp8fgwYObdd7BK08NGDCgXbIBAAAAyRg0aFDMnDkzvvvd70Z9fX28+uqrsXjx4vjYxz4WqVQq6XgAAAAAALQz5SkAANrMsmXLusUctJ2DC1ERueWpdevWZfcXFRU1KkxNmTIlu+pUZWVl9vWGqzc1nONgc+fOzRmXlJTE9OnTD3sOXduKFSuy2xdeeGGzzzu4PGXlKQAAAOh+RowYEVOmTIklS5ZERMRzzz0Xp512Wlx++eUJJwMAAAAAoL3lJR0AAICuq6SkJGecTqe75BxFRUU549ra2jafo62UlpbmjBuu3tRcDc+bMmVKayMd0cGZn3/++ez2E088kd2eNGlSo/MOLjgdfN6aNWuavHZDy5cvzylalZaWxty5cxMtTnWlZ60rqq2tjZdffjkiIvLz82PcuHHNPnf79u3ZbeUpAAAA6J7e8573xPnnn58d33fffVFZWZlgIgAAAAAAOoLyFAAArdawCLJp06YuOUfDgtbGjRtbfI2qqqq2inNYQ4cOzRm/9tprrbrO1q1bc8aDBw9ubaQjes973pPdLi8vb3K74WcQETF8+PAmj33mmWeavHZDB5ezIiKmTZvWzMTtpys9a13RU089ld0+99xzo1+/fs0+9+Dy1IABA9o0FwAAANA5pFKpmD59egwZMiQiIjKZTPz7v/97q7+gCAAAAACArkF5CgCAVmu4gk97lDo6Yo6DSzoRuSsbNdcLL7zQVnEOq2H5ZsWKFa26TkVFRc547Nixrc50JGeccUbOuLKystHn2LAkFxExbNiwnP1VVVWRTqdzsje89sEOLlxFRBQXFzcrb3uWk7rSs9bV1NXVxeOPP54dX3jhhS06f8eOHdltK08BAABA99WnT5+YNWtW9u//b7/9dnz/+99v9GVDAAAAAAB0H8pTAAC02qhRo3LG99xzT5ecY9y4cTnj+fPnRzqdbvb56XQ65s+f39axmtSwTLZ06dIWfzNuOp2OxYsXZ8dFRUXNLha1RmFhYU7pa82aNTkFpdLS0hg4cGCT506aNCm7XVVVFdXV1dlxSUlJFBYWtnneZcuWtfk1D+hKz1pX89xzz2VXjxo8eHC84x3vaNH5B5enrDwFAAAA3dtJJ50Us2bNivz8/IiI2LZtW9xxxx2xe/fuhJMBAAAAANAelKcAAGi1wsLCmDJlSnZcXV0dS5YsadE17rjjjk4xR8MVnQ4uFx1JS45tC3PmzMkZf+9732vR+Q3zfvKTnzzqTEcyYcKE7PaaNWti3bp12fG55557yPNGjhyZ3V63bl3OSk0HX7MpDVezak7JrLKyMpYuXXrE41qrqz1rXUUmk8lZaeyyyy6LVCrVomscKF5FWHkKAAAAeoLhw4fHjTfemB3X1NTEnXfeGfX19QmmAgAAAACgPShPAQBwVK655pqc8fz585tVbqqpqYmysrJmFVU6Yo6ZM2fmjJcuXdqsORYtWtSuZZumTJ48OaeAU1FREXPnzo3a2tojnrtkyZKcvKWlpTF+/Pj2iJlj7Nix2e3y8vKcDIdb9eqMM87Ibi9dujQ2btzY5DWbcvCqVRFHLh5VVlY2Kqa1h670rHUV69atiw0bNkRExLHHHhsXXHBBi69x8MpTylMAAADQM5x//vnx/ve/PzuurKyMX/ziF5HJZBJMBQAAAABAW1OeAgDgqAwbNqxR4WT+/PlRVlYWlZWVkU6ns/vT6XRUVlbGHXfcER/72MeioqKi08xRXFwcs2bNatYctbW1sWLFiigrK8sWchqe294+97nP5aysVF5eHtdff30sWbKk0QpLB+edP39+dn9RUVGUlZV1SN7DFaQO91phYWHO+2xu6SpifzHsYOXl5TF37tyoqqrK2V9VVRWLFi3KPmPTp08/7HWPVld71rqC3/zmN9ntiy66KHr37t2i8+vq6mLXrl0REZFKpeKYY45p03wAAABA53XFFVfEu9/97ux4+fLl8bvf/S7BRAAAAAAAtLX8pAMAAND1TZ48Od56662cYk5FRcURi0stKe90xBxTp06NjRs35hR0mjNHaWlpTJ06NSdbeyssLIy5c+dGWVlZVFdXZ/fPnz+/WTlKS0s7rDh1wPTp0xut/tScotJVV13V6D0157xhw4bFrFmzcs4tLy+P8vLyQ55TWloaN9xwwxFXqTpaXelZ6+yqq6vjhRdeiIiIvLy8uOSSS1p8jZ07d2a3jz322MjL8z0jAAAA0FOkUqn48Ic/HFu2bIlVq1ZFRMS9994bJ554YpxzzjkJpwMAAAAAoC34jTAAANrE1KlT46tf/WrOKkGHM2XKlJg3b94RVw/q6Dlmz54dt9xyS7OPv+WWWzq8hHRAYWFhLFiwoEUrERUVFSWWeeTIkc3a19CIESNadV7E/mem4aplhzJ9+vQOvS9d6VnrzH79619ntydOnBiDBg1q8TW2b9+e3e7fv39bxAIAAAC6kF69esXMmTNj6NChERGRyWTizjvvjFdeeSXhZAAAAAAAtAUrTwEA0GbGjx8f48ePjxUrVsSqVati5cqVOSvpTJkyJYYPHx7jxo2LwsLCTjvHpEmT4p577onVq1fHihUrclYHKioqipKSkhg/fnycffbZMXDgwFbN0ZamTp0al19+eTZvdXV1zj0pLS2NoUOHRklJSYwZMyaxnGeffXaz9jXUVFmuOecdMHny5Jg4cWI88cQT8fzzz+esPFVaWhojRoyISZMmtfp5ORpd7VnrbNavXx+VlZUREZGfnx9XXXVVq66jPAUAAAD069cvZs+eHd/4xjcinU7H3r174//8n/8T//iP/xgnnHBC0vEAAAAAADgKqUwmk0k6BAAAALTU7bffHqtWrYqI/UW4adOmteo6K1asiIULF0ZExHnnnRc333xzm2UEAAAAupbq6uqYN29e7NmzJyIihg4dGp/97GejX79+CScDAAAAAKC18pIOAAAAAC1VWVmZLU717t073ve+97X6Wjt27MhuW3kKAAAAeraioqL42Mc+FqlUKiIiXn311ViwYEHs27cv4WQAAAAAALSW8hQAAABdyp49e+LnP/95dvye97wnBgwY0Orrbd++Pbt9NNcBAAAAuoexY8fmrHC9atWq+NnPfhaZTCbBVAAAAAAAtJbyFAAAAF3Kww8/HJs3b46IiBNOOOGoVp2KsPIUAAAA0Nhll10Wl156aXb8xz/+MR599NHkAgEAAAAA0GrKUwAAAHQZGzdujN/85jfZ8Yc+9KHo3bv3UV3TylMAAABAU6ZNmxbvfOc7s+P77rsvKioqEkwEAAAAAEBrKE8BAADQJdTX18fdd98d+/bti4iIc889N+cXmFpLeQoAAABoSl5eXnzsYx+LU089Nbvvxz/+caxbty7BVAAAAAAAtJTyFAAAAF3Cr371q1i7dm1ERPTp0yeuu+66NrluOp3Obg8cOLBNrgkAAAB0D3369InZs2fH8ccfHxERdXV18f3vfz/+53/+J+FkAAAAAAA0l/IUAAAAnd5LL70UjzzySHY8derUGDRoUJtc++DylJWnAAAAgIaOO+64+PSnPx19+/aNiIhdu3bF7bffHm+88UbCyQAAAAAAaA7lKQAAADq1rVu3xo9//OPsePz48XHRRRe1ybX37NkTe/bsiYiIXr16xTHHHNMm1wUAAAC6l6FDh8anPvWpKCgoiIj9X8byb//2b7F169ZkgwEAAAAAcETKUwAAAHRau3fvjvnz58fOnTsjImLw4MFx/fXXRyqVapPrN1x1qq2uCwAAAHQ/Z511VsycOTPy8vb/mH3Lli3x3e9+N3bs2JFwMgAAAAAADkd5CgAAgE5pz549cccdd0R1dXVERPTu3Ttuvvnm6NOnT5vNcXB5auDAgW12XQAAAKB7euc73xk33XRT9gtYNm7cGN///vdj9+7dCScDAAAAAOBQlKcAAADodOrq6uKHP/xhVFVVRUREKpWKj370ozFkyJA2nWf79u3ZbeUpAAAAoDnGjRsXH/7wh7PjV155JebPnx979+5NMBUAAAAAAIeiPAUAAECnsnfv3rjzzjtj5cqV2X3XX399nH/++W0+18ErTw0YMKDNrw8AAAB0TxdffHG8//3vz47XrFkTCxYsiH379iWYCgAAAACApihPAQAA0Gls27YtvvOd78Tzzz+f3ffBD34w3v3ud7fLfFaeAgAAAFrrfe97X7z3ve/Njl988cX48Y9/HPX19QmmAgAAAACgofykAwAAAEBExPr16+OHP/xhbNu2Lbvvmmuuicsuu6zd5rTyFAAAAHA0pkyZErt27Yo//OEPERHx3HPPRUTEjBkzIi/Pd5kCAAAAAHQGylMAAAAkqr6+PpYvXx5LliyJurq6iIjIy8uL6667LiZNmtSuc1t5CgAAADgaqVQqPvzhD8fbb78dK1asiIj9BapUKhU33XSTAhUAAAAAQCegPAUAAEBi1q1bFz//+c9jw4YN2X0DBgyIm2++OYqLi9t9fuUpAAAA4Gjl5eXFjTfeGBGRLVA9++yzEREKVAAAAAAAnYDyFAAAAB0unU7HL3/5y3jyySdz9p922mnxyU9+MgYNGtRhOQ4YMGBAh8wJAAAAdD8KVAAAAAAAnZfyFAAAAB0ik8nEf/3Xf8Uf/vCH+POf/xz19fXZ1woKCuJ973tfvPe9742CgoIOy2TlKQAAAKCtKFABAAAAAHROylMAAAC0m71790Z1dXWsXr06nnzyydi8eXOjY84///y49tpr44QTTujwbLt27YqI/b/cdMwxx3To/AAAAED3c6gCVSqVihtvvFGBCgAAAAAgAcpTAAAAtFp9fX3s2rUr3nrrrdi5c2e89dZbsWPHjtiwYUOsW7cuqqurY9++fU2eW1xcHH/1V38VZ511Vgen3u/gVacGDBgQqVQqkRwAAABA99JUgWrFihVRX18fN954Y+Tn+zE9AAAAAEBH8q+yAACdwAMPPBAPPPBA0jEAWqxXr16HLEc15dhjj40LLrggLrroohg8eHA7Jjuyg8tTAwcOTDAJAAAA0N00VaB67rnnYvfu3XHzzTdH7969k4xHJ5TJZGJvXX3s3bsv6ur2RX19JurrM5HJZJKOBtCtpVKpyMvb/7/8/F5RUNArCvLzfOEaAABAN6M8BQAAQKs1pzh18sknx/Dhw2PUqFFxzjnnREFBQQckO7J0Op3dVp4CAAAA2lpTBaqXXnopvve978WnPvWp6NevX5Lx6CQymUzs2r03du3aqygFkIBMJhP79mVi376IvXv3xa5d+wtV/foVRL++BUpUAAAA3YTyFAAAAK2Wn58fqVQq8vPzo0+fPjFo0KA4/vjj45RTTonhw4fHGWecEccee2zSMZt08MpTAwYMSDAJAAAA0F0dKFD17ds3Hn/88YiIqKqqittuuy3+5m/+Jvr3759wQpJUV7cv0tt3R3290hRAZ5LJZOKtt/bE7t17Y+CAvpGf3yvpSAAAABylVMZXFwEAANADPfzww3H//fdHRMQVV1wRU6ZMSTYQAAAA0G1lMpm4//7745FHHsnuO+WUU+Jv//Zv4/jjj08wGUl5e09d7NixO/zGBkDnlkpFDOjfN3r39h3lAAAAXVle0gEAAAAgCel0Ors9cODABJMAAAAA3V0qlYr3v//9ce2112b3vf766/Htb387Nm3alGAykrBvX73iFEAXkclEbN+xO/btq086CgAAAEdBeQoAAIAeacuWLdlt3/AMAAAAdIT3vve98ZGPfCRSqVRE7P/3iW9/+9tRU1OTcDI6Unq74hRAV5LJ7P+zGwAAgK5LeQoAAIAeaevWrdlt5SkAAACgo7z73e+OmTNnRq9evSIiYvv27TFv3rxYvXp1wsnoCG+/XWf1EoAuaN+++nj77bqkYwAAANBKylMAAAD0SMpTAAAAQFLOO++8mD17dvTu3TsiInbv3h233357PPnkkwkno73t2rUn6QgAtNKu3f4MBwAA6KqUpwAAAOhx6urqIp1OR0REXl5eDBgwIOFEAAAAQE8zcuTI+Nu//ds45phjIiKivr4+7rrrrrj//vsjk8kknI72UFdXH3VWnQLosurq6qOuzp/jAAAAXZHyFAAAAD3Otm3bstuDBg2KvDx/PQYAAAA63vDhw+Mf//Ef46STTsrue/jhh2PhwoVRV1eXYDLaQ13dvqQjAHCU/FkOAADQNfntMAAAAHqcN998M7t9/PHHJ5gEAAAA6OlOPvnk+PznPx/Dhw/P7nv22Wfj3/7t32Lnzp0JJqOt7fUL9wBdnj/LAQAAuiblKQAAAHoc5SkAAACgM+nfv3/83d/9XZx//vnZfWvXro1vfvOb8cYbbySYjLa0b1990hEAOEr+LAcAAOialKcAAADocbZu3ZrdVp4CAAAAOoOCgoL42Mc+FpMnT87u27RpU3zjG9+IqqqqBJPRVurrM0lHAOAoZXSnAAAAuiTlKQAAAHqcg1eeGjRoUHJBAAAAAA6SSqXimmuuienTp0de3v4f5+/cuTNuu+22eOyxxyKTUb7pynx8AF1fvT/MAQAAuiTlKQAAAHqcLVu2ZLetPAUAAAB0NhMnTozPfOYz0bdv34iIqK+vj5///Odx1113xd69exNOR2spvwF0ff4sBwAA6JqUpwAAAOhxamtrs9uFhYUJJgEAAABo2jve8Y74/Oc/HyeffHJ231NPPRXf+ta3YvPmzQkmAwAAAADoWpSnAAAA6FEymYzyFAAAANAlDBkyJL7whS/E2LFjs/s2bNgQc+fOjVWrViWYDAAAAACg61CeAgAAoEfZsWNH7NmzJyIi+vfvH3379k04EQAAAMCh9evXLz75yU/GX/3VX0UqlYqIiJ07d8b3vve9WLZsWWQymYQTAgAAAAB0bspTAAAA9CibN2/Oblt1CgAAAOgKUqlUXHnllTF79uw45phjImL/6tpLly6NBQsWxO7duxNOCAAAAADQeSlPAQAA0KPU1tZmt5WnAAAAgK5k9OjRUVZWFsOGDcvu+9Of/hT/+q//Gi+//HJywQAAAAAAOjHlKQAAAHoU5SkAAACgKyssLIzPfe5zccEFF2T3vfHGG/Gtb30rHn744aivr08wHQAAAABA56M8BQAAQI9ycHnqpJNOSjAJAAAAQOv07t07brjhhvjQhz4U+fn5ERFRX18f999/f/zbv/1bvPnmmwknBAAAAADoPJSnAAAA6FGsPAUAAAB0B6lUKi655JIoKyuLIUOGZPf/93//d9x6661RUVGRYDoAAAAAgM5DeQoAAIAexcpTAAAAQHcydOjQKCsri8suuyy7b9euXbFgwYK466674u23304wHQAAAABA8pSnAAAA6DHq6urizTffjIiI/Pz8OO644xJOBAAAAHD0CgoK4oMf/GB8+tOfjgEDBmT3P/nkk/G1r30tXn755eTCAQAAAAAkTHkKAACAHmPTpk2RyWQiYv+qU6lUKuFEAAAAAG1n9OjRccstt8SYMWOy+95444345je/Gffcc0/s2bMnwXQAAAAAAMlQngIAAKDH2LhxY3Z78ODBCSYBAAAAaB8DBgyIT33qU/GhD30oCgoKIiIik8lEeXl5/O///b9j1apVCScEAAAAAOhYylMAAAD0GAeXp4YMGZJgEgAAAID2k0ql4pJLLomysrI4/fTTs/s3b94ct99+eyxatCh27tyZXEAAAAAAgA6kPAUAAECPYeUpAAAAoCcZMmRIfO5zn4tp06ZF7969s/ufeuqp+MpXvhLPPfdcZDKZBBMCAAAAALQ/5SkAAAB6jNdffz27rTwFAAAA9AR5eXlRWloa/+t//a8YNWpUdv/27dvj3//932P+/PmxdevW5AICAAAAALQz5SkAAAB6hEwmky1PpVKpOOWUUxJOBAAAANBxTjzxxPj0pz8dN910Uxx77LHZ/S+++GL8y7/8SzzyyCOxd+/eBBMCAAAAALQP5SkAAAB6hDfffDP27NkTEft/WaigoCDhRAAAAAAdK5VKxYQJE+JLX/pSTJgwIbv/7bffjl/+8pfxla98JSoqKiKTySSYEgAAAACgbSlPAQAA0CNs3Lgxuz148OAEkwAAAAAkq3///nHTTTfFpz/96TjhhBOy+zdv3hwLFiyIefPmRXV1dYIJAQAAAADajvIUAAAAPYLyFAAAAECu0aNHx5e+9KW45pprok+fPtn9a9euja9//euxaNGi2LZtW4IJAQAAAACOXn7SAQAAAKAjvPrqq9lt5SkAAACA/QoKCmLy5MkxceLEuP/+++PJJ5+MTCYTmUwmnnrqqaioqIj3ve99cfnll0dBQUHScQEAAAAAWkx5CgAAgB5hw4YN2e1hw4YlmAQAAACg8xk4cGBMnz49Lr300rjnnntizZo1ERGxZ8+e+NWvfhXLly+PK664Ii666CIlKmgDJxUOyBm/Ubs9oSQ9Q1L32+cMAAAAnUNe0gEAAACgvdXV1WVXnurVq1cMHTo04UQAAAAAndOwYcPi7/7u72LWrFlx0kknZfdv27Yt/vM//zP+1//6X1FeXh579+5NMCUAAAAAQPNZeQoAAIBu77XXXot9+/ZFRMTQoUMjP99fhwEAAAAOJZVKxdixY2PUqFGxfPnyePDBB+Ott96KiIh0Oh333HNPLFu2LN773vfGxRdfHL179044MQAAAADAofltMQAAALq9DRs2ZLeLiooSTAIAAADQdeTn50dpaWlMnDgxfv/738dvf/vb2LlzZ0TsL1Hde++9sWzZsrj88svjkksuUaICAAAAADol5SkAgBa44oorcsbLli1LKEnn5R4BnVF1dXV2W3kKAAAAoGX69u0bkydPjksvvTSWL18ejz76aOzYsSMiIrZv3x733Xdf/OY3v4nS0tK46KKLon///gknBjpabe0bUfHcs/Hoo8viG9/8TtJxAAAAAHIoTwEAANDtWXkKAAAA4Oj17ds3rrjiimyJ6je/+U1s3749IiJ27NgR999/fzz44IMxbty4uPTSS/07DPQQ//j5f4iFCxdkx8pTAAAAQGejPAUAQJfQcEWrwyktLY2hQ4dGSUlJjBkzph1TAV1BfX191NTUREREr1694i/+4i8STgQAAADQtfXu3Tsuv/zymDRpUvzhD3+IZcuWRTqdjoiIurq6eOqpp+Kpp56KM844Iy699NI477zzIj/frydAd3VwcQoAAACgM/KvkwAAdDvl5eUREbF48eKIiJgzZ05Mnjw5yUhAgl5//fXYu3dvREQMHTrUL+oAAAAAtJHevXtHaWlpXHzxxfHkk0/GY489Fq+99lr29fXr18f69evj3nvvjYsuuiguvvjiOO644xJMDAAAAAD0RH5jDACAbm/evHnx/PPPx8yZM6OwsDDpOHRjtbW18eyzz8bvf//7mDt3btJx+L9eeeWV7HZRUVGCSQAAAAC6p4KCgpg0aVJcfPHFsWbNmnjsscfiz3/+c2QymYiISKfT8eCDD8bDDz8c5513XlxwwQUxcuTI6NWrV8LJAQAAAICeQHkKAIAeoby8PLZu3arQQrspKyuLioqKpGPQhKqqquz2aaedlmASAAAAgO4tlUrF2WefHWeffXZs2bIlHn/88fjDH/4QO3fujIiI+vr6eO655+K5556L/v37x/nnnx/jx4+PM844I1KpVMLpAQAAAIDuSnkKAIAuadmyZU3uT6fTsWnTpnjhhRdi/vz5Oa9VVFTEkiVLYurUqR0RkR5GcarzOrg8VVxcnGASAAAAgJ7jhBNOiPe///1x1VVXxXPPPRe/+93vYsOGDdnXd+zYEY899lg89thjceKJJ8b48eNjwoQJMXjw4ARTAwAAAADdkfIUAADdysCBA2PgwIFRXFwckyZNigULFkR5eXn29fnz58fll18eAwcOTDAl0FEOFCojIgYMGBCnnHJKwokAAAAAepaCgoJ417veFRdccEGsX78+nnnmmXjuueeyq1FFRGzevDkefvjhePjhh2PYsGExYcKEOP/88+P4449PMDlt7aTCATnjN2q354yffXZFPPPMU/Glf/5iRERceeXV8d4rJkdJybgYPXrMIa9bW/tGPP74Y7F69X/Ft7/19ey577rw3XHJJZcd9tzmSKfTsWbN6njmmafi5fXrYuHCBdnXPvu5L8TZZ78jxo+/IIYNO/Wo5mmOl16qjEsvubDR/h/+aGFce+20Zl1j7dqqeOGF53PuV0TEjBkz451jzzni/Y5o/Fm25PWGn3tDSd3vmpoNsWLF043uy7985WvxzneOjXPOOS/Rny21xed2KIe652353xEAAAAkLZXJZDJJhwAA6CquuOKKnPGhVj/qydrrHrX2uul0OubMmRPV1dXZfXPmzInJkye3SS44wJ8PndOf/vSn+NGPfhQREeedd17cfPPNCScCAAAAYN++fbFq1apYsWJF/PnPf449e/Y0edzQoUNj9OjRMXr06Bg+fHjk53ft74et3bwj6QiJOlR5qqZmQ3zx//t8PPTQA4c891++8rWYPftvGu1f9shD8ZGPXHfYeWfMmBn/+IUvRmHhSS3Km06n47e/XRafuHlGs44/VMZDOVKZrKG1a6viXRec12h/c4tTNTUb4rv/Ni+njHQoV155dfzt3302xo0b3+TrRypPHc6h3meS9/uuu34cc/7hyNdact+v4+KLL2n2nEeatzna8nNryn333dOse37llVfHl758a5x5ZnGzr92dFZ7YP+kIAAAAtFBe0gEAAKA9DRw4MG644YacfevWrUsoDdDRqqqqsttnnXVWgkkAAAAAOKBXr14xZsyYmDFjRnzjG9+Ij33sY/HOd74z8vJyf4Xh1Vdfjd/85jdx2223xec///n4wQ9+EH/4wx/izTffTCg5bW3t2qo479xRhy1ORUR86Z+/GHPn3pqzb+7cW49YnIqIWLhwQcz5h7+JdDrd7FwvvVQZn/n0J5pd5DmQ8R8//w/NPr4lamvfiH/58i2N9je3OLXskYfivHNHNauAExHx0EMPxJWTS+O+++5pcdbWSPJ+z517a7OKUxERU6/9y7jjjtuPes7mas/Prbb2jbjhox9u9j1/6KEHmizvAQAAQFfRtb+WCQAAmmHUqFE544qKioSSAB1NeQoAAACgc+vdu3eMGzcuxo0bFzt37oyKiop47rnnoqqqKurr67PHvf322/HnP/85/vznP0dExJAhQ2L06NExcuTIOP3006Nfv35JvQVaKZ1ON1kIOpRvf+vr8e53XxwXX3xJLHvkofj2t77e7HMfeuiBWLz4P5q9UtGll1zY7GsfbOHCBXH6GcNbtCLSkaTT6ZjzD3/TqGDW3OJUc1cWasonbp4Rxx5zbFzxvitbdX5zJXW/5869tUXPUcT+0taQIUOade+PRnt/bk09UwAAANCdpTKZTCbpEAAAXcUVV1yRM162bFnOeMWKFbFixYpYunRpdl9JSUlMmDAhJkyYEMOGDWv13Ol0OlavXh0rVqyI6urqnAJQaWlpjBgxIsaOHRvFxcWtun5tbW2sXLkyKisro6KiIqqrq7OvTZkyJcaPHx/jx48/4nWOdI8aqqysjDlz5uTsmzVrVkydOvWortuaXIc7Zvny5fHggw9GRUVFFBUVxd///d/HmDFjDjtnZWVlrFmzJtasWRPl5eXZ/UVFRVFSUhLDhw+PcePGRWFhYYveS3PeT3s9i+39HKbT6XjiiSdi3bp1jbKPGjUqSkpKcu57a5+LtngfDeduriNlrK2tjWeffbbRPTiQ62j/LOlJdu/eHZ/97Gcjk8nEscceG9/4xjcilUolHQsAAACAZti1a1f813/9V6xcuTJeeuml2Lp16yGPTaVSMXjw4DjjjDOy/xs8eHCjlaySVrt5R9IREnVS4YCc8b985WvxpX/+Ylx55dVx8yc+Feecc14MHDgwIiJqajbE737320YrAl155dXxtX/9Zpx37v/70rQf/mhhXHzxJVFYeFJE7F9R5/HHH2uyeLJ23f9k52hu1hkzZsbll18Ro0aPiWHDTs3uT6fT8ec//yl+9MP/06iEsuq/1mXzNGeOiIg3arc3eVxTBZ/mFqeefXZFXDm5NGfflVdeHdOn39jo/dTWvhGrVq1s8v386fmVOce29r005/yOut9L7vt1TL32LyMiss/gyJGjcq6zdm1VPPLIQ/Glf/5io+sd6Z4cat7m3Jv2/twef/yx7Hs/YN53bo+JEy+KM8/8fz8XSafT8cYbm+KFF57P/vfU0s+2uyo8sX/SEQAAAGgh5SkAgBY4VFFjxYoV8YMf/CCncNSUKVOmxOzZs1s0ZzqdjkcffTTmz5/frONLS0tj5syZzS7k1NTUxP33359T0jiU5pSGWlJmqa2tjeuvvz5n36HuUVLlqdra2igrK2vysz1UhuXLl8eiRYuO+DwcMGXKlLjuuutaVKJqi2dx+vTpzfohcUT7P4cREYsWLYrFixcf8biSkpL4zGc+E8OGDWvxc9GW76M9ylPNvQeteWZ6opUrV8b3vve9iIgYO3ZszJo1K+FEAAAAALRGJpOJ1157LV566aV46aWXGq1K1ZS+ffvGaaedllOo6t8/2V92V54a0GjflVdeHfO+c/shiy/LHnkoPvKR6xqdc6Ak8vvHnozRo5v+mcVLL1U2WtFoyX2/josvvqRZWWfMmBk33vTxQ17/gNraNxqt4nP33b844mpNzSnV3HHH7Y2KO/O+c3t89KM3HeEd7P/38DOH/0XOvn/5yteatUpTw8LWkc5ri/JUR9/vA89Rc4poTT1Ln/3cF6Ks7Mgrp7X03nTE5/aPn/+HWLhwQXb80MPlMW7c4b9AMZ1Oxy9/uaRZz15PoDwFAADQ9ShPAQC0QFNFjSVLljS7iBGxv4A0d+7cZpUeKisr47bbbmt2CefgOebNm3fEYszDDz8c8+bNa9G1Iw5f/mhumSWdTsecOXNy3ltpaWmUlZUd1XWPJldTx5SVleWsSnS4a6TT6bjjjjtyVplqiXnz5h1xNavDZW2vZ7G9n8PDFdQO54477mhUtDvcc9HW76Mty1OtuQct+bOkp1qyZEk8+uijERHxgQ98IN7znvcknAgAAACAtrB79+5YvXp1rFy5MtauXRuvvfZaNOdXHwYOHBgnn3xynHLKKTF48OA45ZRT4pRTTokTTzyxQ1apUp5qXJ566uk/5ax005SGRY8DmlP4aFg+am4J5b777mnWyk4HNFzJpznzHKlUc9999zRaPau5hZ2IiLvu+nHOyl3NLV0d0PC+H251p6MtTyVxvyOav4JXU3NGtO0KYwd0xOd2tJ8XylMAAABdUX7SAQAAurLly5dnyyolJSUxffr0KCoqypYsampq4plnnskptFRXV8eCBQsOWRI62Jw5c7LbJSUlcemll8aYMWNi2LBh2f3pdDqef/75nJWOqqurY/HixYdd5aqpok1JSUl84AMfiDPOOCOnkFFTUxOVlZVxzz33tLh4cih33HFHzrWKiopavCpXc1VVVeWMp0yZ0qzzli9fHhUVFVFUVBSf/OQnY/z4/T+Era2tjV/84heNjm9YBouImDVrVkyYMCHnM6utrY3169fHvffem1PMmjNnTosKVA2zttez2J7PYVOloaKiopg2bVqjOaqqqmLZsmXZVdLmzp17pNvSru+jYQmqtQW/dDrd6B4c+AwPfhYqKytj8eLF2Wemuro6ysrKYsGCxr80wH4vvPBCdnvEiBEJJgEAAACgLfXt2zfOOeecOOeccyJif5nqlVdeifXr18fLL78c69evj+3bG5cB0ul0pNPpRv9m3KtXrzjppJOyhaqTTz45jjvuuBgwYEAMHDgwBgwY0CHlqp7mX77ytSMWpyIirvvQ9Y3KUzNmzDxicSoi4pJLLssZv7x+XbOytaTIExExcuSonPFTT/6xWSWtQ3n88ceOqjiVTqdzCjhXXnl1i1cManjfV61a2axVu1ojift95ZVXt2jeiy++JGbMmNmu96SrfW4AAADQlShPAQAchVtvvTUi9hdkpk6d2uj1YcOGxbBhw2LEiBE5xY3y8vKYOHFiTJo06YhzNFWiONjAgQNj0qRJMWrUqLj++uuz+5cuXRrXXHNNTjHkgIOLNgd89atfzZaDDvU+Jk+eHIsWLTpi5iNZsmRJo9WZ5s6de8QVilrr4AJFRMTw4cObdd6iRYuaXN2nsLCwUZFm7ty5jVbRmjlzZpOrAhUWFkZhYWGMHz++UYnttttua9ZqTQ2197PYHs9hRMSCBQsa3bfZs2c3+f6Li4ujuLg4xo8fH//0T//UqiJfe72Po9GwSHioz3DMmDExd+7cmDt3bva/n+rq6liyZEmTx/d0mzZtik2bNkVExPHHH98unx0AAAAAnUPfvn3j7LPPjrPPPjsiIjKZTGzZsiWnTLVhw4aoq6tr8vx9+/bFxo0bY+PGjU2+nkql4thjj80pUx38f/v27Rv5+fmRn58fBQUF2f97YPvAmFwNi02HMnjw4Eb7rvvQ9U0c2dhxxx2XM164cEF845vfada5LdFwZZ+HHnqg1dd66aXKRisctaQ4FRGxZs3qnPHf/t1nW5xjxIizc8YvvvhCpynhtMX9vvkTn2rxOQ2LSW19Tzrqc/vs574Q3/7W17Pjlq78BQAAAF2R8hQAwFGaPn36EYsLY8aMiVtuuSVbcInYX8w5UmHlUCWKphQWFsasWbNyijjPPPNMo8JATU1NTo6IaNFqRzfccEOzjjuUFStWNCpuzZs3r8mSUVuorKxsNN+4ceOadW51dXV89atfPWK25cuX55TBioqKmrWyWETE1KlTY+PGjdnVlKqrq+PRRx9tVRmmuc/iV7/61finf/qn7L4jPYvt8RxGtP6+jR8/vtF7aI72eh9HY8WKFTn3YMqUKUfMWFZWFlVVVdnC1fz58+Pyyy9vt/JhV/Xiiy9mt8eOHRupVCrBNAAAAAB0pFQqFSeeeGKceOKJ2X8Prq+vjy1btsTrr7/e6H/btm077PUymUzs2LEjduzYEa+99lqrc33lf3+j1ed2R6ecckqzjhs27NRG+04//fRWn9tWamo2xLZt22LLls3x8svr2+SatbVvxKWXXJizr6XFqYiIVateyhk3LNQ0R8N/c27uql3tpa3vd8PVq5qjYZGvre9JR31ul1/+vpzy1CdunhFPPvHHuPGmj8fo0c37eSEAAAB0NcpTAABHoaioqNllokmTJkVJSUlUVFRExP6STGVl5WFLSy0t0EyYMCGn7NHUt2Tef//9OeNbbrml2cWpo1VTU9Oo8DJnzpx2m3/FihWN5psyZUqzi1olJSWHXI3rYA1X42puceqA6dOnZ8tTEa0rw7TkWRw/fnyjZ7GqqiqKi4ubPL49nsOIiAcffDBn3JL7Nn78+JgyZUrOfTuS9nofR+Pee+/NGU+fPr1Z502bNi3mzZuXHa9evbpZz2pP0rA8BQAAAEDPlpeXF4WFhVFYWBijR4/OeW3Xrl2xadOmeP3112Pjxo1RW1sb6XQ6tm/fHul0Onbu3JlQ6u6t4epBHXVuS9XWvhGrVq2Ml19eH9u3b48v/fMX222eOf/wNzn7WlOcioh48YU/54zPHP4XR5Utov1W7Wqoo+53a56hhmW8tr4nHfW5jRs3vtHqUwsXLoiFCxfElVdeHddOnRYXX3xJh/53BgAAAO1NeQoA4ChMmzatRcdfeuml2cJKRMSaNWvatDjUcFWcpUuXxuzZs7PjdDqdUzYpKio64upXbaW2tja+/OUv5+ybPn16TJ48uU3nqampiddeey3uvffenHsdsf/9NrecErH/8zqSg1cAiogoLS09ZAnpUAYOHBjTp0+PxYsXZ/e1tAxztM/iCy+80OLch3Kk5zBi/307eP6SkpIWzz9p0qQWladaqjnv42g0vAezZs1qdmGu4Z8bq1atUp46yK5du6KqqioiIvr27RtnnXVWwokAAAAA6Mz69esXp512Wpx22mlNvr5v377YsWNHTqFq+/btsW3bttixY0fs2bMn9u7dG3V1dVFXV5fdbvh/6Vpeeqky/uPH/x4LFy7okPkWLPhBPPTQA9nxlVdeHbNn/22rrtVRmdtSR9/vzqgj33tZ2S0xcOBxjcppDz30QPY5nDFjptWoAAAA6DaUpwAAjkJLi08Nj2+PlWwO5/nnn88Zt7RwczQWLFjQqGTU3JWSmnLFFVe0+Jwvf/nLLVrNqTmf74GCxgHvec97WpwrYn956ODyVEvLMF3tWWx436666qoWX6OjVkxrLw3vQUtWR2pY7Hr11VfbJFN3sXLlyqivr4+IiNGjR0d+vr/6AgAAANB6vXr1iuOOOy6OO+64o7pO7eYdbZSI9nbXXT9utApUU2bMmBmnnzE8is8sjo985LqjmvPgVYAiIkaNHtOin2l0ZUncbyJmz/6buOSSyw5ZWjuwGtVnP/eFmDnzk1aiAgAAoEvzG2QAAEehYYGhpce3diWbmpqa2Lp1a2zZsiVqa2tj48aNUVFRkVNOakplZWXOuKPKJ4sWLYry8vLsuKioKMrKyjpk7gPzzZ07NwoLC1t0XnN+KLlu3bqc8ZAhQ1o0xwGDBg3KGbe0DJPEs9ja5zCi8X0bPnx4i+ZuS0fzPo5Gw3twNCt/lZeXd+h/U53diy++mN1uSSkNAAAAAOC+++5pVOSZMWNmXDjx3XHqqafF4MGDY+DA49q82PT7x56MSy+5MDs+UKYqK7ulTefpbJK63+w3evSY+MY3vxM33vTxqKh4tskS27e/9fX49re+Hr9/7EmrUAEAANBlKU8BAHQBVVVV8cILL8SDDz54VIWOhue2tHDTGsuXL89ZUelAkamjzJo1K6ZOndqqc5vzg7ilS5fmjFt7Txue1xnLMG31HEY0fhY78oeebfk+jkbDZ6c1q6nR2N69e7Plqby8vC6/QhkAAAAA0HFqajbEJ26ekbPvoYfLY9y48e0+9+jRY2LJfb+Oqdf+ZXZfWxWo3qjdflTnt5ck73dr1NRsyBl/9nNfaNf5OvJzGz16TIwePSbe//6p8ec//yl+df/SRqtRfX3urfG97/9QkQ0AAIAuSXkKAKATq62tjQULFuSs2nQ0Kioq2uQ6LXHrrbfmjG+44YYWrwDVEkVFRVFSUhLjx4+Ps88+2w9w2kBbP4cRjZ/Fjvic2uN90Pm88MILsWvXroiIOOuss6Jfv34JJwIAAAAAuooVK57OGS+579cdWuS5+OJL4oc/WphTKGpNgepfvvK1+NI/fzE7rq19IwoLT2q7oG0k6fvdUhs3bswZ/8VftO2XFHaGz23gwIFx8cWXxMUXXxJ/dc2UnDLfQw89EL/97bK49tppHZoJAAAA2oLyFABAJ1VVVRWzZ89u8rWSkpIoKiqK4cOHxzHHHBPDhw+PiP2rF3W21WtKS0tzyiqLFi2KUaNGHXWBatmyZUcbjWboLs9hd3kfHNlTTz2V3Z4wYUKCSQAAAACArubJJ/6YM7744kuadV7DFYmOxoFiytEUqIYMGZIzfvnllztleSrJ+712bVWceWZxi8559NFHcsYjR44+6hwH62yf28UXXxIPPVweV04uze578ok/Kk8BAADQJSlPAQB0oHQ6nTMuKio65LFz587NGZeUlMT06dNjzJgx7ZKtvcycOTOqqqqiuro6IiKqq6vjW9/6VqP3R8dq7rPYXZ7DrvA+FAKP3rZt22LlypUREdGnT58oKSlJOBEAAAAA0JUsXLigVec1XEHpaF177bRYvfq/sqWpiJYVqEaMeEfO+Bc//0mnXNEpyfv9xBN/aFF5qqZmQ87nERFx+umnH3WOg3XGz63h/AsXLohvfPM7CaUBAACA1stLOgAAQE/SsLByqF/sX758ebZsFLF/9aa5c+ceddGj4Xw1NTVHdb3mKCwsjLKyspx9FRUV3aY8VVpamjNu7T1teN6UKVNaG6lZmvMsttdzGNG4rFVbW3vU1zyU9nwfR6PhPW/4mdByTz/9dGQymYiIGDduXPTp0yfhRAAAAABAV9acf7etqdmQs0pUWykruyU++7kv5Oz79re+Hvfdd88Rzx09ekxceeXV2fHChQuadV5D6XQ65s69tcXn1da+0eJzDsx3JG11v+f8w9/ESy9VNvv4xYv/I2f82c99oc1XhUr6cwMAAIDuTHkKAKADrVu3Lmc8fPjwJo974okncsbTpk1rk/lHjRqVM37ttdfa5LpHUlxcHHPmzMnZV15eHkuWLOmQ+dvT0KFDc8atvadbt27NGQ8ePLi1kZqlOc9iez2HEY2LQxs3bmzxNaqqqpp1XHu+j6PRsEC2adOmhJJ0D5lMJp566qns+MILL0wwDQAAAADQFc2YMTNn/MtfHv7nGDU1G+KL/9/n2y1PWdktjTJ94uYZzSrU3PyJT7XqvAOefXZFfObTn2i02lJTDi78REQ8/vhjzZoj6ft96SUXNqtANXfurY3uw1/91ZQ2y3Gwjvjc7rjj9mYX3J59dkXOuGGhDwAAALoK5SkAgKPQ3PLGAQ1LHMXFxU0eV15e3qzjWppn5MiROePf/va3zbpuW5g8eXKjVZrmz5/f5QtUDUtAK1asOMSRh1dRUZEzHjt2bIvOb49nsb2ew4jGZa01a9Y069oHe+GFF5p1XHu+j6PRcOWr9p6vu3vllVeyJbzBgwfHGWeckXAiAAAAAKCruXDiu3PGc/7hb2Lu3Ftj7drcf79du7Yq7rvvnjjv3FHx0EMPxL985Wvtlukfv/DFRuWk5hRqLr74kiaLVzd89MOx7JGHoqZmQ6Nzamo2xLJHHop//Pw/xJWTS+Ohhx5oVsb3XjG50TzLHnkop6Czdm1Vo9WQkrzfB+7NpZdcGHfccXujOWtr34jHH38sbvjohxsVkf7lK1+L0aNz/42/rXTE5/alf/5ijHzH8Jg799Z49tkVTV7zwD2/cnLuz/Yuv/x9rXhXAAAAkLz8pAMAAHRly5Yta3YRo6amJqfEUVRU1OxzW5LncMaPH58zLi8vj+nTp8ewYcPaNMehlJWVRVVVVVRXV2f3zZ8/P0aMGNGoSNJVNMy9dOnSuOaaa1p0T9PpdCxevDg7bs2z0ZmexSM9hxGNC0zz58+Pyy+/PAYOHNisOdLpdDz44IOtytdczXkfR6PhSnD33HNPTJ48+RBHcyQHFwInTpwYqVQqwTQAAAAAQFc0fvwFjfZ9+1tfP+wqPldeeXVMn35jfOmfv9gumQoLT4p537k9IiKnFPOJm2dERMS110475Ln/+IUvxsaNr+Wc99BDDzS7FBXReFWpppSUjGu07yMfua7JY8vKbsluJ3m/Pznr07Fw4YKI2F8mau71rrzy6pg9+2+Oau4j6ajP7Uj3uqHPfu4LMW7c+CMfCAAAAJ2QlacAAI7C0qVLo7KyslnHHlyOiYi44YYbDnlsUVFRzrimpuaI16+srIylS5ce8bg5c+bkjL/85S9HbW3tEc9rK1/+8pcb7ZszZ06XXnWn4T393ve+16LzGz4bn/zkJ1ucoT2exfZ8DouLixut2tUw1+EsXrw4p4R3OO35Pg43z5H+uyosLIwpU6Zkx9XV1S1eie2OO+5o0fHdVTqdjqeffjoiIvLy8mLChAkJJwIAAAAAuqJhw06Nu+/+RYvO+ULZLc3+YrDWKiw8Kb705Vsb7T/SClQHilfNKdI05corr84Wtw5n9Ogx8dnPfaHF10/yfp95ZnH88EcLW3TOjBkzm3U/jlZHfW4tMWPGzJg5s+U/vwIAAIDOQnkKAOAo3XbbbUcs/ixatKjRSj+TJk065PENXztSqaSysrJRgedQJk+enFNaqa6ujrKysmYVStLpdCxatKhZ8xzKsGHD4pZbbmm0f+7cuR1a4mpLDe9pRUVFs9/PkiVLcko6paWljVYIa67WPIslJSWHfBbb8zmMiJg5c2bOeOnSpc0qDy1atKhFxab2fh8HNCyDrVy58ojnXHPNNTnj+fPnN+se1NTURFlZWYsLXt1VeXl57N27NyIixo4d2+6/qAAAAAAAdF9XvO/KWHLfr4943JVXXh1PPf2nGD16TAek2l/2+f1jTzba35wC1fe+/8MWF4V++KOFseiun0Vh4UnNOr6s7JYjFqiaKgMleb+vvXZas+aO2H8/vvHN7zT7fhyt9vzcnnr6TzFjxsxDvt7UNTvyvQMAAEB7SGUymUzSIQAAuoorrrgiZ1xUVJRd/WbWrFkxYcKEGDZsWETsLxpVV1fH4sWLo6KiIue8O++8M3tcU2pqauJjH/tYzr7S0tKYNm1aFBcXZ/dVVVXFE088kS2DTJ8+vVExZNmyZY2uX1tbG2VlZY1W7pk+fXpMnDgxTj755JzyQVVVVbzwwgsxf/78Q17zgIb36FDHLlq0qFHWoqKiWLBgwVFd92gczRyHuqcNn4sDx65fvz7uvffenGfjcO//SFnb41ls7+cwYn957MBzdUBJSUlMnz49ioqKss/hgXv2gx/8IPs+58yZE/PmzTviPB3xPiIiVqxYEf/0T/+Us++rX/1qtgxXW1sbv/jFL2L27Nk5xzz88MON3kdT9+DA57h8+fKc0lR7/LfQlbz11ltxyy23xO7duyMi4gtf+EKcdtppCacCAAAAgMZqN+9IOkKiTiockDN+o3Z7pz43nU7HU0/+MSr+9Fx8+1tfz+7/l698LSZMeFeMG5f7RWgtnae1uV56qTIuveTCRvt/+KOFce210w57bjqdjjVrVsczzzwVTz35x3jooQeyr82YMTPeOfacGDlydKP31hIvvVQZFRXPxm+WPZy9/owZM+PCie+O97znikN++VWS9/twcxefWRzvuvDdrf7SrqN5dg/O1x6f20svVcaaNf8Vq1f/V877PviaI0ac7QvLmlB4Yv+kIwAAANBCylMAAC3QsLDyk5/8pMnCzOHMmzcvxow58rfiNVUqOZzS0tIoKytrdgHoUGWf5miL8lRERFlZWaMyz4H3cTTXba2jneNo7umh3vehdNSz2N7PYUTEHXfc0eIVlGbNmhVTp05t9jwd8T4imn6mG2rqGi3NF7G/MFdWVpZTAOuJHnzwwfj1r/d/M+iYMWMaldMAAAAAoLPo6eUpgO5CeQoAAKDryUs6AABAV1ZYWBhz586NkpKSIx5bUlISd955Z7OKUxERU6dOjTlz5jTr2OnTp7eoeBOxP/uCBQti1qxZzT6npKQk7rjjjhbNczif+9znoqioKGdfeXl5LFq0qM3m6EituadFRUVxyy23tPjza2ru9ngW2/s5jIiYPXt23HLLLc06tqioKL761a/G1KlTWzRHR7yPiKaf6YMd6rWpU6fGV7/61cOee7ApU6bEvHnzenxx6u23347f/e532fGVV16ZYBoAAAAAAAAAAAA6o/ykAwAAdHUHSiuVlZWxfPnyqKioyK7+U1JSEqNGjYqSkpJml6YONnny5Jg4cWI88cQT8fzzz0d5eXn2tdLS0hgxYkRMmjQpCgsLW51/6tSpcfnll8fq1atj1apVsXLlypyVcw7MM3bs2DYvahQWFsbf//3fNyq1LF68OPr379/igkxncfA9XbFiRVRXVze6p0OHDm3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      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=3407x1675 at 0x4193F10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(IMG.open('searchnet.png'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nn import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['__class__',\n",
       " '__del__',\n",
       " '__delattr__',\n",
       " '__dict__',\n",
       " '__dir__',\n",
       " '__doc__',\n",
       " '__eq__',\n",
       " '__format__',\n",
       " '__ge__',\n",
       " '__getattribute__',\n",
       " '__gt__',\n",
       " '__hash__',\n",
       " '__init__',\n",
       " '__init_subclass__',\n",
       " '__le__',\n",
       " '__lt__',\n",
       " '__module__',\n",
       " '__ne__',\n",
       " '__new__',\n",
       " '__reduce__',\n",
       " '__reduce_ex__',\n",
       " '__repr__',\n",
       " '__setattr__',\n",
       " '__sizeof__',\n",
       " '__str__',\n",
       " '__subclasshook__',\n",
       " '__weakref__',\n",
       " 'backPropagate',\n",
       " 'feedforward',\n",
       " 'generatehiddennode',\n",
       " 'getallhiddenids',\n",
       " 'getresult',\n",
       " 'getstrength',\n",
       " 'maketables',\n",
       " 'setstrength',\n",
       " 'setupnetwork',\n",
       " 'trainquery',\n",
       " 'updatedatabase']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(searchnet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dtanh(y):\n",
    "\t\treturn 1.0-y*y\n",
    "\n",
    "class searchnet:\n",
    "\t\tdef __init__(self,dbname):\n",
    "\t\t\tself.con=sqlite.connect(dbname)\n",
    "\t\n",
    "\t\tdef __del__(self):\n",
    "\t\t\tself.con.close()\n",
    "\n",
    "\t\tdef maketables(self):\n",
    "\t\t\tself.con.execute('create table hiddennode(create_key)')\n",
    "\t\t\tself.con.execute('create table wordhidden(fromid,toid,strength)')\n",
    "\t\t\tself.con.execute('create table hiddenurl(fromid,toid,strength)')\n",
    "\t\t\tself.con.commit()\n",
    "\n",
    "\t\tdef getstrength(self,fromid,toid,layer):\n",
    "\t\t\tif layer==0: table='wordhidden'\n",
    "\t\t\telse: table='hiddenurl'\n",
    "\t\t\tres=self.con.execute('select strength from %s where fromid=%d and toid=%d' % (table,fromid,toid)).fetchone()\n",
    "\t\t\tif res==None: \n",
    "\t\t\t\t\tif layer==0: return -0.2\n",
    "\t\t\t\t\tif layer==1: return 0\n",
    "\t\t\treturn res[0]\n",
    "\n",
    "\t\tdef setstrength(self,fromid,toid,layer,strength):\n",
    "\t\t\tif layer==0: table='wordhidden'\n",
    "\t\t\telse: table='hiddenurl'\n",
    "\t\t\tres=self.con.execute('select rowid from %s where fromid=%d and toid=%d' % (table,fromid,toid)).fetchone()\n",
    "\t\t\tif res==None: \n",
    "\t\t\t\tself.con.execute('insert into %s (fromid,toid,strength) values (%d,%d,%f)' % (table,fromid,toid,strength))\n",
    "\t\t\telse:\n",
    "\t\t\t\trowid=res[0]\n",
    "\t\t\t\tself.con.execute('update %s set strength=%f where rowid=%d' % (table,strength,rowid))\n",
    "\n",
    "\t\tdef generatehiddennode(self,wordids,urls):\n",
    "\t\t\tif len(wordids)>3: return None\n",
    "\t\t\t# Check if we already created a node for this set of words\n",
    "\t\t\tsorted_words=[str(id) for id in wordids]\n",
    "\t\t\tsorted_words.sort()\n",
    "\t\t\tcreatekey='_'.join(sorted_words)\n",
    "\t\t\tres=self.con.execute(\n",
    "\t\t\t\"select rowid from hiddennode where create_key='%s'\" % createkey).fetchone()\n",
    "\n",
    "\t\t\t# If not, create it\n",
    "\t\t\tif res==None:\n",
    "\t\t\t\tcur=self.con.execute(\n",
    "\t\t\t\t\"insert into hiddennode (create_key) values ('%s')\" % createkey)\n",
    "\t\t\t\thiddenid=cur.lastrowid\n",
    "\t\t\t\t# Put in some default weights\n",
    "\t\t\t\tfor wordid in wordids:\n",
    "\t\t\t\t\tself.setstrength(wordid,hiddenid,0,1.0/len(wordids))\n",
    "\t\t\t\tfor urlid in urls:\n",
    "\t\t\t\t\tself.setstrength(hiddenid,urlid,1,0.1)\n",
    "\t\t\t\tself.con.commit()\n",
    "\n",
    "\t\tdef getallhiddenids(self,wordids,urlids):\n",
    "\t\t\tl1={}\n",
    "\t\t\tfor wordid in wordids:\n",
    "\t\t\t\tcur=self.con.execute(\n",
    "\t\t\t\t'select toid from wordhidden where fromid=%d' % wordid)\n",
    "\t\t\t\tfor row in cur: l1[row[0]]=1\n",
    "\t\t\tfor urlid in urlids:\n",
    "\t\t\t\tcur=self.con.execute(\n",
    "\t\t\t\t'select fromid from hiddenurl where toid=%d' % urlid)\n",
    "\t\t\t\tfor row in cur: l1[row[0]]=1\n",
    "\t\t\treturn l1.keys()\n",
    "\n",
    "\t\tdef setupnetwork(self,wordids,urlids):\n",
    "\t\t\t\t# value lists\n",
    "\t\t\t\tself.wordids=wordids\n",
    "\t\t\t\tself.hiddenids=self.getallhiddenids(wordids,urlids)\n",
    "\t\t\t\tself.urlids=urlids\n",
    " \n",
    "\t\t\t\t# node outputs\n",
    "\t\t\t\tself.ai = [1.0]*len(self.wordids)\n",
    "\t\t\t\tself.ah = [1.0]*len(self.hiddenids)\n",
    "\t\t\t\tself.ao = [1.0]*len(self.urlids)\n",
    "\t\t\t\t\n",
    "\t\t\t\t# create weights matrix\n",
    "\t\t\t\tself.wi = [[self.getstrength(wordid,hiddenid,0) \n",
    "\t\t\t\t\t\t\t\t\t\tfor hiddenid in self.hiddenids] \n",
    "\t\t\t\t\t\t\t\t\t for wordid in self.wordids]\n",
    "\t\t\t\tself.wo = [[self.getstrength(hiddenid,urlid,1) \n",
    "\t\t\t\t\t\t\t\t\t\tfor urlid in self.urlids] \n",
    "\t\t\t\t\t\t\t\t\t for hiddenid in self.hiddenids]\n",
    "\n",
    "\t\tdef feedforward(self):\n",
    "\t\t\t\t# the only inputs are the query words\n",
    "\t\t\t\tfor i in range(len(self.wordids)):\n",
    "\t\t\t\t\t\tself.ai[i] = 1.0\n",
    "\n",
    "\t\t\t\t# hidden activations\n",
    "\t\t\t\tfor j in range(len(self.hiddenids)):\n",
    "\t\t\t\t\t\tsum = 0.0\n",
    "\t\t\t\t\t\tfor i in range(len(self.wordids)):\n",
    "\t\t\t\t\t\t\t\tsum = sum + self.ai[i] * self.wi[i][j]\n",
    "\t\t\t\t\t\tself.ah[j] = tanh(sum)\n",
    "\n",
    "\t\t\t\t# output activations\n",
    "\t\t\t\tfor k in range(len(self.urlids)):\n",
    "\t\t\t\t\t\tsum = 0.0\n",
    "\t\t\t\t\t\tfor j in range(len(self.hiddenids)):\n",
    "\t\t\t\t\t\t\t\tsum = sum + self.ah[j] * self.wo[j][k]\n",
    "\t\t\t\t\t\tself.ao[k] = tanh(sum)\n",
    "\n",
    "\t\t\t\treturn self.ao[:]\n",
    "\n",
    "\t\tdef getresult(self,wordids,urlids):\n",
    "\t\t\tself.setupnetwork(wordids,urlids)\n",
    "\t\t\treturn self.feedforward()\n",
    "\n",
    "\t\tdef backPropagate(self, targets, N=0.5):\n",
    "\t\t\t\t# calculate errors for output\n",
    "\t\t\t\toutput_deltas = [0.0] * len(self.urlids)\n",
    "\t\t\t\tfor k in range(len(self.urlids)):\n",
    "\t\t\t\t\t\terror = targets[k]-self.ao[k]\n",
    "\t\t\t\t\t\toutput_deltas[k] = dtanh(self.ao[k]) * error\n",
    "\n",
    "\t\t\t\t# calculate errors for hidden layer\n",
    "\t\t\t\thidden_deltas = [0.0] * len(self.hiddenids)\n",
    "\t\t\t\tfor j in range(len(self.hiddenids)):\n",
    "\t\t\t\t\t\terror = 0.0\n",
    "\t\t\t\t\t\tfor k in range(len(self.urlids)):\n",
    "\t\t\t\t\t\t\t\terror = error + output_deltas[k]*self.wo[j][k]\n",
    "\t\t\t\t\t\thidden_deltas[j] = dtanh(self.ah[j]) * error\n",
    "\n",
    "\t\t\t\t# update output weights\n",
    "\t\t\t\tfor j in range(len(self.hiddenids)):\n",
    "\t\t\t\t\t\tfor k in range(len(self.urlids)):\n",
    "\t\t\t\t\t\t\t\tchange = output_deltas[k]*self.ah[j]\n",
    "\t\t\t\t\t\t\t\tself.wo[j][k] = self.wo[j][k] + N*change\n",
    "\n",
    "\t\t\t\t# update input weights\n",
    "\t\t\t\tfor i in range(len(self.wordids)):\n",
    "\t\t\t\t\t\tfor j in range(len(self.hiddenids)):\n",
    "\t\t\t\t\t\t\t\tchange = hidden_deltas[j]*self.ai[i]\n",
    "\t\t\t\t\t\t\t\tself.wi[i][j] = self.wi[i][j] + N*change\n",
    "\n",
    "\t\tdef trainquery(self,wordids,urlids,selectedurl): \n",
    "\t\t\t# generate a hidden node if necessary\n",
    "\t\t\tself.generatehiddennode(wordids,urlids)\n",
    "\n",
    "\t\t\tself.setupnetwork(wordids,urlids)      \n",
    "\t\t\tself.feedforward()\n",
    "\t\t\ttargets=[0.0]*len(urlids)\n",
    "\t\t\ttargets[urlids.index(selectedurl)]=1.0\n",
    "\t\t\terror = self.backPropagate(targets)\n",
    "\t\t\tself.updatedatabase()\n",
    "\n",
    "\t\tdef updatedatabase(self):\n",
    "\t\t\t# set them to database values\n",
    "\t\t\tfor i in range(len(self.wordids)):\n",
    "\t\t\t\t\tfor j in range(len(self.hiddenids)):\n",
    "\t\t\t\t\t\t\tself.setstrength(self.wordids[i],self. hiddenids[j],0,self.wi[i][j])\n",
    "\t\t\tfor j in range(len(self.hiddenids)):\n",
    "\t\t\t\t\tfor k in range(len(self.urlids)):\n",
    "\t\t\t\t\t\t\tself.setstrength(self.hiddenids[j],self.urlids[k],1,self.wo[j][k])\n",
    "\t\t\tself.con.commit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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